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"name": "",
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Table of Contents\n",
"\n",
"* [Definition of Terms](#termdef)\n",
"* [Week 1](#week1)\n",
"* [Week 2](#week2)\n",
" * [Statistical Linear Regression Models](#statisticallinearregressionmodels)\n",
" * Interpreting Regression Coefficients\n",
" * Statistical Regression Models Examples\n",
" * Residuals\n",
" * Properties of Residuals\n",
" * Residual Variation\n",
" * [Inference in Regression](#inferenceinregression)\n",
" * [Tests for Regression Coefficients](#testsforregressioncoefficients)\n",
" * [Prediction of Outcomes](#predictionofouctomes)\n",
" * [Confidence Intervals (provisional)](#confidenceintervals)\n",
" * [Quiz 2](#quiz2)\n",
"* [Week 3](#week3)\n",
" * [Multivariate Regressions](#multivariateregressions)\n",
" * [Examples](#multivariableregressionexamples)\n",
" * [Interactions](#interactions)\n",
" * [Multivariate Regressions Simulations](#multvarsimulations)\n",
"\n",
"* [Week 4]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" \n",
"# Term Definitions\n",
"TODO: Complete\n",
"\n",
"* $\\hat Y$ : Predicted $Y$, aka the fitted value\n",
"* $\\bar Y$: Sample Mean\n",
"* $\\mu$: Population Mean\n",
"* $\\beta_n$: model coefficient\n",
"* $s$\n",
"* $\\sigma$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" \n",
"# Coursera Regressions Week 1"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Least Squares"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import rpy2\n",
"from IPython.display import YouTubeVideo\n",
"%load_ext rpy2.ipython\n",
"%matplotlib inline"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"The rpy2.ipython extension is already loaded. To reload it, use:\n",
" %reload_ext rpy2.ipython\n"
]
}
],
"prompt_number": 15
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"heig = pd.DataFrame.from_csv('data/Galton.csv', index_col=None)\n",
"heig = pd.melt(heig, value_vars = ['child', 'parent'], value_name = 'height')"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R -i heig\n",
"require(ggplot2)\n",
"df <- as.data.frame(heig)\n",
"g <- ggplot(heig, aes(height, fill=variable)) + geom_histogram(binwidth=1) + theme_bw()\n",
"g <- g + facet_grid(~variable)\n",
"\n",
"g"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"Loading required package: ggplot2\n"
]
},
{
"metadata": {},
"output_type": "display_data",
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XW6xyMuttq1xb+Tr11/w1wNguR8vzKsNtvs5zm59eb+e1zWe/OoRZbrHKCbPO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\nAElFTkSuQmCC\n"
}
],
"prompt_number": 3
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Find the middle via least squares"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let $Y_i$ be the height of child $i$ for $i = 1, ..., n = 928$ then define the middle as the value of $\\mu$ that minimizes\n",
"\n",
"$\\sum\\limits_{i=1}^n (Y_i - \\mu)^2$\n",
"\n",
"* The middle gives us the 'physical' center of mass of the graph\n",
"* You might have guessed that the answer that minimizes the squared distance above is $\\mu = \\bar{Y}$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Experiment\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$\\sum\\limits_{i=1}^n (Y_i - \\mu)^2$\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's try different values of $\\mu$ to see where the minimal value is above"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"child = heig[heig['variable'] == 'child']"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import numpy as np\n",
"child.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"
\n",
"
\n",
" \n",
" \n",
" \n",
" variable \n",
" height \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" child \n",
" 61.7 \n",
" \n",
" \n",
" 1 \n",
" child \n",
" 61.7 \n",
" \n",
" \n",
" 2 \n",
" child \n",
" 61.7 \n",
" \n",
" \n",
" 3 \n",
" child \n",
" 61.7 \n",
" \n",
" \n",
" 4 \n",
" child \n",
" 61.7 \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 5,
"text": [
" variable height\n",
"0 child 61.7\n",
"1 child 61.7\n",
"2 child 61.7\n",
"3 child 61.7\n",
"4 child 61.7"
]
}
],
"prompt_number": 5
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"hrange = np.arange(child['height'].min(), child['height'].max(), .5)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 6
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"MSE = lambda x: ((child.height - x)**2).mean()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 7
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"MSEdf = pd.DataFrame([(_, MSE(_)) for _ in hrange], columns = ['mu', 'MSE'])"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 8
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Let's plot different values for $\\mu$ and see what we get"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"pd.DataFrame.plot(MSEdf, x = 'mu', y='MSE', title='Minimizing Mu');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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2hDVuDI8/7ga5ufDC8A3JakyuFi508zH+4Q/RbayzsRp2iRQ716ZN3dn1Z5/B\nVVe5q+d+iMtnanmW3rffur7WV13lhkwttCDlmomdYUdI8+bw4ovwj3+4q+fGRMUPP8Cvfw2HHQZ9\n+vgdjX+shh1BX37pZqy59FK45hq/ozGmYdascY31Vlu5oRmaxKAzckOmCBstIktE5MOUdQNFZGGt\nGWhMQOy8M0yc6GatefRRv6MxJn+rVrkeUNts48bSiUNjnU0uJZHHgNoNsgLDVbWz93glnzcPQ82o\nUEqda7t28OqrcPPNrrZdKnH5TC3P4vv+e3eBcaedXH/rYvd+CsNnWuffK1V9U0TK07y0xem6CZYO\nHVw/1aOPhu22c8NOGhMGy5e7xrp9e/ctMQ53MeYipxq212C/qKr7eMu3ABcA3wLvAX1UdVma/ayG\nHQD/+Af06OFG+vvlL/2Oxpjsvv3W3b37i1/AAw9EZ3qv+ij0WCKjgNu857cDw4CL0m1YVVVFeXk5\nAGVlZVRUVFBZWQls+gpiy8VffvJJOPHEBEOHwsUX+x+PLdtyuuXly+H22ys56CA49dQEb7wRrPiK\ntZxIJKiurgbY2F6mpap1PoBy4MM8XtNsJk2alPX1KAlCrn/+s2rbtqozZxbvPYKQZylYnoX33/+q\ndu6sevXVqhs2lOxtNwrSZ+q1nVu0qXl92RCRtimLpwAfZtrWBMevfw3Dh7txg994w+9ojNnkyy/h\niCPcdZZhw9w4OWZLddawRWQs0BVoBSwBbgEqgQpcb5F5wG9VdUmafbWu45vSe+01OOssN6b2aaf5\nHY2Ju0WL4Fe/cncvDhxojTVkrmHbjTMxNX26uwp/441w+eV+R2PiauFCd2bds6f7WTROIAd/Shbd\n4yBouXbu7GarGTECbrqpcGOPBC3PYrE8G+6zz6CyEi65JBiNdRg+0xh2mDFJP/mJ6/L36qtw8cWw\nbp3fEZm4+PRT11hfeaWbONfkxkoihhUrXP2wSRN3+28hZu8wJpNPPnE16/793VR3ZkuBLImYYGjR\nwk2z1LKl+0X66iu/IzJRNXs2dOsGt9xijXU+rIZdIkHPdautoLrafU099FCYPz+/4wQ9z0KxPOtv\n4kT38zVoEFyU9jY7f4XhM4352FcmlQjcdRe0besa7b/9DTp18jsqE3aqrm/1sGFueNSuXf2OKLys\nhm3SeuYZuOIK9693J60x9bZypesFMmcOPP887Lab3xGFg9WwTb2ccYa7AHnGGfDnP/sdjQmjzz5z\n39QaNYLgHjvWAAAMJklEQVQpU6yxLgSrYZdIGHPt1s11+bv6arjvvtz2CWOe+bA869oPDj4YzjvP\nTRC9zTYFDasowvCZWg3bZFVR4c6OjjnGnTHddVfxB5I34aUKI0fCnXfCk0+6cWtM4VgN2+Tkq6/c\n2dKyZTB2LGQbAdLE0+rV8LvfuWEPxo93kw+Y/FgN2zRIq1au18jpp8NBB1ld22xu4UI38fOqVfDW\nW9ZYF4vVsEskCrk2auRmYX/pJbjhBnf1//vvN98mCnnmwvLcZMoU90f8tNPgT3+CbbctflzFEIbP\n1M6wTb0dcAB88AGsWeOez5zpd0TGLw88AKeeCqNHw/XX29CoxWY1bNMgTzzhzroHDnTDtNovbDys\nWQO9ernBw8aPh5/+1O+IosXGwzZF88knbkKEXXd1M1zvtJPfEZli+vxz93m3bg1jxsB22/kdUfTk\nfdFRREaLyBIR+TBlXUsRmSgic0XkVREpyyeoMNSMCiXKue65p7vQtMcesNdeCSZP9jui4ovy55kq\nNc/16+Hee2G//aB7d3j22Wg11mH4THOpYT8GHFtrXT9goqp2AF7zlk2MNW3qxoq49lo480w3GpuN\nrx0dM2fC//wPjBvnyiD9+rmL0Ka0ciqJiEg58KKq7uMtzwG6quoSEWkDJFR1rzT7WUkkhhYvdn22\nV6+Gp56yW5LDbNUquO02V+oaNAguvNAa6lIodD/s1imT7i4BWucdmYmcNm1gwgQ3Z+QBB8Bzz/kd\nkcnHa6/BPvu42WFmznSzEllj7a8G35quqioiGU+jq6qqKPduiysrK6OiooJKb/i3ESNGbLacrCFF\ncTm1PhaEeIq1XFNTQ+/evWnUCLp0STBwIPTtW8nYsdCjR4JddglWvPkuR/nz3GefSvr0gZdfTnDS\nSTU8/HDvQMVXrGU/26NEIkF1dTXAxvYyLVWt8wGUAx+mLM8B2njP2wJzMuyn2UyaNCnr61ESl1zT\n5blypeqdd6rutJPqNdeoLl1a+rgKLYqf54YNqk8+qdq6tWrv3qrLl0czz0yClKvXdm7RpuZbwx4C\nfK2qg0WkH1CmqltceLQatkm1ZIm7GPncc+5Oycsvdxcrjf/mzXNTdi1eDA8/DAce6HdE8daQbn1j\ngbeAjiKyQEQuAO4GjhKRucAR3rIxWbVu7e6MmzTJDdu6996u8ba/6f5Ztw5+/3vXQHfrBu++a411\nkNXZYKvqWar6Y1VtqqrtVPUxVV2qqkeqagdVPVpVl+Xz5ql1wKiLS6655Ln33m48kvvvd3dIdu3q\nGoowicLn+d57bgyQCRNg2jR3a3ntoXOjkGeuwpCrXfM1vjnqKDcUZ8+e0KMHnHOOG3PbFI8qTJ4M\nJ5zgbn7p3dt929ljD78jM7mwW9NNIKxYAUOHusHvL73U3Zixww5+RxUdGzbAX/4CgwfD0qXQt6/r\nK9+smd+RmXRsPGwTaC1awK23uv6+ixdDx46uZGJ3SzbMmjXuppef/9zNFtS3L8ye7YbGtcY6fGw8\n7BKJS64NzXOXXeCxx+Dll91t0D/7GQwZ4nqYBEnQP89vv3X/bz/5iRvz44EHXJ36tNOgcePcjxP0\nPAspDLnaGbYJpM6d4e9/d6PB/fOfsNdecMopbtYbO+vObNEiV076yU9gxgx3cffll6Gy0oa+jQKr\nYZtQWL4cnn7afb3//HOoqnLjWtjFMmfuXHcNYNw4OPdcN0a5zbsZXlbDNqG23XZuLIu333a9Glat\ngkMOgSOOcANMrVrld4Slt2qVO3s+7TQ49FBXTpo71w2Bao11NFkNu0Tikmsp8tx7bxg+HBYscHfn\nPfEEtGsHV1zhugmWgl+f54IFrh7dvbu7Eemuu9wNL/PmuT7trVoV9v3i8nML4ci1wYM/GeOXrbd2\ns7iffrorkzz2mOvP3aoVXHQRnHyyO+sMs3XrYOpUV7v/29/giy/g2GPh7LNdfb9lS78jNKVkNWwT\nKevXu2FBR492/269NRx8sHt06QL77w/Nm/sdZXZLl8Irr7gGesIEN/XaCSe4R5cu9evlYcLJ5nQ0\nsaPqxnKeNs2dpU6dCh9/7HqcdOmyqSHfc09/e1CsWOFqzxMmuEZ65kzXq+OEE+D44125x8RLIBvs\nRCKxcWzYqItLrkHPc/VqV+dObcS/+25TA96li5uzsGVLaJKlYFifPL/9FubPd7fdp/6bfL5yJbRv\n7y6gnnCCa6yDclNL0D/PQgpSrpkabKthm1hp1sz1LjnkkE3rFi/e1IAPGQI1Na6RbdrU3YGZ7rFi\nhetm2KKF68GSXP/991s2yuvXw+67u54b5eXu+cEHb1r3ox9ZH2mTGyuJGJOGqjsbX7Ei+2P58s2f\nN2++qVFO/tuypTXIpn4CWRIxxhizpaLcOCMi80VkpohMF5F36rt/GPo9FkpccrU8oyUueUI4cm3o\njTMKVKpqZ1U9qL4719TUNPDtwyMuuVqe0RKXPCEcuRbiTse8q3PLluU1UU0oxSVXyzNa4pInhCPX\nQpxh/11E3hORSwoRkDHGmPQa2q3vl6q6SER+BEwUkTmq+mauO8+fP7+Bbx8eccnV8oyWuOQJ4ci1\nYL1EROQWYIWqDktZZ11EjDEmDwW9cUZEmgONVXW5iGwLHA3cWtcbGmOMyU9DSiKtgefF3RHQBHhK\nVV8tSFTGGGO2UNQbZ4wxxhROSScwEJEyEXlWRGaLyCwROVhEhnrLM0TkORHZoZQxFUO6PFNe6yMi\nG0Qk9CMZp8mzi7f+Sm/dRyIy2O84CyHDz+5BIvKud+PYuyJyoN9xNoSIdPRyST6+FZFeItJSRCaK\nyFwReVVEyvyOtSEy5HlVKNoiVS3ZAxgDXOg9bwLsABwFNPLW3Q3cXcqYSpWn97wd8AowD2jpd5xF\n+jy7AROBrbz1P/I7ziLmmgCO8dYdB0zyO84C5tsIWOT9zA4BrvPWXx+F39EMeQa+LSrZGbb31+ow\nVR0NoKrrVPVbVZ2oqhu8zaYBu5YqpmLIlKf38nDgOt+CK6AseV4G3KWqa731//UxzILIkusiXMMN\nUAb8x6cQi+FI4F+qugA4CfcHC+/fHr5FVXhHAv9W1QVhaItKWRJpD/xXRB4TkQ9E5GGvp0mqC4GX\nShhTMaTNU0ROBhaq6ky/AyyQdHluC+wJHC4iU0UkISIH+BxnIWT62e0HDBORz4GhQH9foyysM4Gx\n3vPWqrrEe74E1+EgKs4E/phmfSDbolI22E2A/YD7VXU/4HvcDzwAInIj8IOqpvvPC5N0ed6K+2W+\nJWW7sHd5zPR5NgF2VNWDgb7AM/6FWDDpcu0PPAr0UtXdgKuB0f6FWDgi0hToDvy59mvq6gWR6KmQ\nKc8gt0WlbLAX4s4w3/WWn8X9EiAiVcDxwDkljKdY0uXZGSgHZojIPNxXrfdFZGd/QiyITHkuAJ4D\n8F7bICI7+RNiwWT62T1IVZ9PWVfvAdAC6jjg/ZRy1hIRaQMgIm2BL32LrLBq5xn4tqhkDbaqLgYW\niEgHb9WRwMcicizuTOxkVV1dqniKJUOe76tqG1Vtr6rtcQ3Afqoa2h/8TJ8n8BfgCADvtaaq+rU/\nURZGllw/EZGu3rojgLl+xFcEZ7GpHALwAtDTe94TGF/yiIpjszzD0BaVtB+2iHQCHgGaAv/G1Yne\n9ZaXepu9raqXlyyoIkiT5wUpFx4RkU+BA1R1aYZDhEK6PIGVuNJABfAD0EdVE37FWCgZct0T+AOw\nNbAKuFxVp/sWZAF41yE+A9qr6nJvXUtcaWs3YD5whqoGf2i7LDLk+QkBb4vsxhljjAmJkt44Y4wx\nJn/WYBtjTEhYg22MMSFhDbYxxoSENdjGGBMS1mAbY0xIWINtjDEhYQ22McaEhDXYJrJEpFxE5nij\n7P1TRJ4SkaNF5C1vMP4DRWSgiPRJ2ecjEdnNz7iNyaQhczoaEwZ7AKcBs3DDIPxGVf9HRE4CbgBq\nam1vt/6awLIzbBN181T1Y29Y0I+Bv3vrP8KNoGhMaFiDbaJuTcrzDbgBqZLPmwDr2Pz3oFmJ4jKm\n3qzBNnE3n03jsu+Hm13GmECyBttEXe2atNZ6Pg5oKSIfAf8L/LNUgRlTXza8qjHGhISdYRtjTEhY\ng22MMSFhDbYxxoSENdjGGBMS1mAbY0xIWINtjDEhYQ22McaEhDXYxhgTEv8P/PiISXTICxsAAAAA\nSUVORK5CYII=\n",
"text": [
""
]
}
],
"prompt_number": 9
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"child.mean()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 10,
"text": [
"height 68.08847\n",
"dtype: float64"
]
}
],
"prompt_number": 10
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"** The math follows as **\n",
"\n",
"$$\n",
"\\begin{align}\n",
"\\sum_{i=1}^n (Y_i - \\mu)^2 & = \\\n",
"\\sum_{i=1}^n (Y_i - \\bar Y + \\bar Y - \\mu)^2 \\\\\n",
"& = \\sum_{i=1}^n (Y_i - \\bar Y)^2 + \\\n",
"2 \\sum_{i=1}^n (Y_i - \\bar Y) (\\bar Y - \\mu) +\\\n",
"\\sum_{i=1}^n (\\bar Y - \\mu)^2 \\\\\n",
"& = \\sum_{i=1}^n (Y_i - \\bar Y)^2 + \\\n",
"2 (\\bar Y - \\mu) \\sum_{i=1}^n (Y_i - \\bar Y) +\\\n",
"\\sum_{i=1}^n (\\bar Y - \\mu)^2 \\\\\n",
"& = \\sum_{i=1}^n (Y_i - \\bar Y)^2 + \\\n",
"2 (\\bar Y - \\mu) (\\sum_{i=1}^n Y_i - n \\bar Y) +\\\n",
"\\sum_{i=1}^n (\\bar Y - \\mu)^2 \\\\\n",
"& = \\sum_{i=1}^n (Y_i - \\bar Y)^2 + \\sum_{i=1}^n (\\bar Y - \\mu)^2\\\\\n",
"& \\geq \\sum_{i=1}^n (Y_i - \\bar Y)^2 \\\n",
"\\end{align}\n",
"$$\n",
"\n",
"* $\\bar{Y}$ : different guesses for $\\mu$\n",
"* $\\mu$ : value that minimizes $\\sum\\limits_{i=1}^n (Y_i - \\mu)^2$\n",
"\n",
"He adds and subtracts $\\bar{Y}$ and then expands and simplifies.\n",
"\n",
"The end result is that for any arbitrary $\\mu$, the sum will be greater than the sum when $\\bar{Y} = \\mu$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Comparing childrens' heights and their parents' heights"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# reimport so I don't have to unmelt\n",
"heig = pd.DataFrame.from_csv('data/Galton.csv', index_col=None)\n",
"# get counts of values for the bubble plot\n",
"h = pd.DataFrame({'count' : heig.groupby( [ \"child\", \"parent\"] ).size()}).reset_index()\n",
"h[:10]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"
\n",
" \n",
" \n",
" \n",
" child \n",
" parent \n",
" count \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" 61.7 \n",
" 64.0 \n",
" 1 \n",
" \n",
" \n",
" 1 \n",
" 61.7 \n",
" 64.5 \n",
" 1 \n",
" \n",
" \n",
" 2 \n",
" 61.7 \n",
" 65.5 \n",
" 1 \n",
" \n",
" \n",
" 3 \n",
" 61.7 \n",
" 68.5 \n",
" 1 \n",
" \n",
" \n",
" 4 \n",
" 61.7 \n",
" 70.5 \n",
" 1 \n",
" \n",
" \n",
" 5 \n",
" 62.2 \n",
" 64.5 \n",
" 1 \n",
" \n",
" \n",
" 6 \n",
" 62.2 \n",
" 66.5 \n",
" 3 \n",
" \n",
" \n",
" 7 \n",
" 62.2 \n",
" 67.5 \n",
" 3 \n",
" \n",
" \n",
" 8 \n",
" 63.2 \n",
" 64.0 \n",
" 2 \n",
" \n",
" \n",
" 9 \n",
" 63.2 \n",
" 64.5 \n",
" 4 \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 11,
"text": [
" child parent count\n",
"0 61.7 64.0 1\n",
"1 61.7 64.5 1\n",
"2 61.7 65.5 1\n",
"3 61.7 68.5 1\n",
"4 61.7 70.5 1\n",
"5 62.2 64.5 1\n",
"6 62.2 66.5 3\n",
"7 62.2 67.5 3\n",
"8 63.2 64.0 2\n",
"9 63.2 64.5 4"
]
}
],
"prompt_number": 11
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R -i h\n",
"require(ggplot2)\n",
"require(hexbin)\n",
"df <- as.data.frame(h)\n",
"g <- ggplot(df, aes(parent, child, size=count)) + geom_point() + ggtitle(\"Bubble Plot of Height\")\n",
"g + theme_bw()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"Loading required package: hexbin\n"
]
},
{
"metadata": {},
"output_type": "display_data",
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4nQAXYfm9hlk+EiABEiABTxKgAvZktVAoEiABEiABvxOgAvZ7DbN8JEACJEAC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\n"
}
],
"prompt_number": 12
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Regression through the origin"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Suppose that $X_i$ are the parent's heights"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Consider picking the slope $\\beta$ that minimizes"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$\\sum\\limits_{i=1}^n (Y_i - X_i\\beta)^2$ -- this in effect is trying to minimize the error value $\\epsilon$\n",
"\n",
"This is using the origin as a pivot point picking the line that minimizes the sum of the squared vertical distances of the points to the line\n",
"\n",
"A line through the origin is:\n",
"\n",
"$y = x\\beta$\n",
"\n",
"* It has a y-intercept of 0.\n",
"* the slope is $\\beta$\n",
"* $x_i\\beta=\\hat{y}$ is the fitted value\n",
"* $y_i - \\hat{y}$ is the vertical distance between the data point and the fitted line\n",
"* is it NOT the orthoganol distance\n",
"* we don't really want the line go through the origin\n",
"* if we subtract the means so that the origin is the mean of the parents' and child's heights, then going through the origin makes sense\n",
"* the origin is the average of both variables\n",
"\n",
"\n",
"\n",
"* $\\mu$: population mean\n",
"* $\\bar X$: sample mean\n",
"* $\\sigma$: population standard deviation\n",
"* $s$: sample standard deviation"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"col = 'child'\n",
"h[col] = h[col] - h[col].mean()\n",
"col = 'parent'\n",
"h[col] = h[col] - h[col].mean()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 13
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R -i h\n",
"require(ggplot2)\n",
"require(hexbin)\n",
"df <- as.data.frame(h)\n",
"g <- ggplot(df, aes(parent, child, size=count)) + geom_point() + ggtitle(\"Bubble Plot Height De-meaned\") + theme_bw()\n",
"g2 <- geom_smooth(data=df, aes(parent, child, weight=count), colour='red', method=lm, se=FALSE)\n",
"g3 <- geom_smooth(data=df, aes(parent, child), colour='green', method=lm, se=FALSE)\n",
"g4 <- geom_smooth(data=df, aes(parent, child), colour='blue', method=loess, se=FALSE)\n",
"g + g2 + g3 + g4 + theme(legend.position=\"none\")"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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A/fr1MaxwHimkTZvWsPLMUBDfkvgmee7cOU2x5c6d2wxiGSJDsPuL6+eRLyuf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\n"
}
],
"prompt_number": 14
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Note the difference in the linear fit when the size of the dots is considered.\n",
"* red = size considered\n",
"* green = size not considered\n",
"* blue = loess"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Find the best $\\beta$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"find:\n",
"\n",
"$\\min\\sum\\limits_{i=1}^n (Y_i - X_i\\beta)^2$\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"col = 'child'\n",
"heig[col] = heig[col] - heig[col].mean()\n",
"col = 'parent'\n",
"heig[col] = heig[col] - heig[col].mean()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 15
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"MSE = lambda beta: ((heig['child'] - heig['parent'] * beta)**2).mean()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 16
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# try slopes between -3 and 3\n",
"betas = np.arange(-3, 3, .01)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 17
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df = pd.DataFrame([(beta, MSE(beta),) for beta in betas], columns = ['beta', 'MSE'])"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 18
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df.plot(x = 'beta', y='MSE', title = 'finding the best Beta empirically');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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kNCYaJk2Cnj1h7NiaN9bJ2KXpaQijjta6tZuh5txz4ZNPsruvqNQJa8Pn3MDy\nC9N338E//gEPPgjFxZndtjXYEdS+Pdx/P3TubGNoG5NLfv0VOnVy0/917pz57VsNO8KGDHF1snfe\ngaZNw47GmPy2dq1rpAsL3dF1OicZaz2WSDqswc4uVTjnHDcuwahR0MDOSBgTClU3Rsi337rzTOlO\nQmITGGRB2HU0ETfw+apV7gRHpr8bw84vm3zODSy/ujZ4MEye7IZHzuaMUdZgR1yjRvDcc+6s9A03\nhB2NMflnxAhXAnn55dqPEZIqK4l4YtEi+Otf3dVUZ50VdjTG5IexY+H00yEWg912y9x2rR+25woL\n3SS+HTpAixbw97+HHZExfps2DU47zf3CzWRjnYyVRNKQa3W0Nm1cH+0zz3QlknTlWn6Z5HNuYPll\n29dfu4Oiu++Gv/2t7vZrDbZn9t/fjVvQuTPMmRN2NMb4Z+FCOPJIuO46NzBbXbIatqeGD3cDz0yY\nAK1ahR2NMX5YtsyVHU8+2TXY2WI17Dxz1lmwYoU7EnjnHdh667AjMiba/vc/VwY54gjo0yecGKwk\nkoaw62jV6dXLHQkcdRQsX1796yvK9fzS4XNuYPll2u+/wz//CbvsArfdlpmhUmvDGmzP9e/vfsL9\n/e/uCMEYUzPr1rkhjTfeGIYNq93kuZliNew8UF7uLmGfP99dNrvRRmFHZEw0lJfDeee5XiGvvAKN\nG9fNftOZImy4iCwWkekJj/UXkfkVZqAxOapePXdk0KyZm329LqcZMyaqVN0MT59/DqNH111jnUwq\nB/cPAxUbZAXuUNV9gttrmQ8t90WpTli/Pjz+uGusu3VLrdGOUn415XNuYPmlSxUuucRdHPPKK7kz\nGma1DbaqTgCWVfJUSGV3U1uNGsGzz7pa9mmnueEgjTF/puqm4Js4EV59Nfvjg9RESjVsESkCxqhq\n22C5H3AmsAKYDFyhqhv0Q7Aadm5atcrNiNGsGTz2mA3LakycKlx7LbzxBrz1FjRvHk4cme6HfS8w\nMLg/CLgdOLuyF5aWllJUVARAQUEBxcXFlJSUAOt/1thy3S8//zwcckiMjh3hjTdKaNAgt+KzZVuu\n6+Xx42MMHw6fflrCuHEwbVrd7T8Wi1FWVgbwR3tZKVWt9gYUAdNr8Zz6bPz48WGHkJaVK1U7dlQ9\n9VTVNWs2fD7q+SXjc26qll9NlZerXnON6p57qv7wQ0Y3XStB27lBm1qrHoUi0jJh8R/A9Kpea3JX\n48ZusKhMfMK7AAAOiElEQVQff4Tu3a33iMlPqnDZZW6o1FgMttoq7IiqVm0NW0RGAh2ALYHFQD+g\nBCjG9RaZC5yvqosrWVer274J38qVcNJJrpb95JO50X3JmLpQXg4XXACffupOMBYUhB2RY3M6mqR+\n/90NxL5smTvqbtIk7IiMya61a+Hss2HePHjppRzrDWJzOmZe/KSBDxo1gpEj3ch+Rx3lBo7yKb+K\nfM4NLL/qrFnjurYuXJh7XfeSsQbb/KF+fTc3Xbt2cNhhrtE2xje//QYnnOCuRxg9GjbZJOyIUmcl\nEbMBVTc35AsvuP6o224bdkTGZMbSpXD88bDjjm7M+GzOcJ4OK4mYlInA4MFQWuom9p0xI+yIjEnf\n/PlwyCFw4IFupvNcbayTsQY7Db7XCdu3jzF4sCuPTJgQdjSZ5ftnZ/n92axZcNBB7iDkttvCHSI1\nHREN29SV0093l6//859udmhjombiRDj0UBg0CK68Muxo0mM1bJOSKVPguOPcOAs9e4YdjTGpefFF\nNxZ8WZmbxCMqrB+2SdvcuXD00dClC9x0U3R/Vhr/qcKdd8Ltt7uT5+3bhx1RzdhJxyzItzrhDjvA\ne+/B++/DiSdGe8qxfPvsfJMsvzVr3NWLZWXwwQfRa6yTsQbb1MiWW8Kbb7pLeA8+GL77LuyIjFlv\nxQpX+vj2W3j3XWjdOuyIMstKIqZWVN3PzTvvhFGjYP/9w47I5Lu5c915lsMPhzvuiPY471YSMRkl\n4s6433ef+08ycmTYEZl8Nm6c61/9r3/BXXdFu7FOxhrsNORznTDu+OPdzBzXXutu69ZlP65MsM8u\n2uL5qbqj6dNOgyeegIsvDjeubLMG26Rtr73go4/c7aijYMmSsCMy+eC331xD/dhj8OGH7gIv31kN\n22TMunXw73+72dmfeQb22y/siIyv5s5185K2bQsPPAAbbxx2RJllNWyTdfXrw403uhricce5+rZ9\nX5tMe/FFOOAAOPNMeOQR/xrrZKptsEVkuIgsFpHpCY9tLiJjRWSOiLwhIjkyT0Pdypc6YU117uz6\na99zjxu7IRf7a9tnFz2//w69esEll0DfvjEuvdSd/M4nqRxhPwwcXeGx3sBYVW0DvBUsG/OHv/zF\n1RVFYN993aXtxtTW3Lmu3/9XX7m/pT32CDuicKRUwxaRImCMqrYNlmcDHVR1sYgUAjFV3bWS9ayG\nbXjiCTfJaZ8+5OVRkUnPqFGuu96117q/o3z4+0lrLJFKGuxlqto8uC/A0vhyhfWswTYAfP01dOsG\nW2wBDz8MW28ddkQm1/38s2ug33nHncjOp4uzqmqw0+5erqoqIlW2yqWlpRQVFQFQUFBAcXExJSUl\nwPo6W1SXhw4d6lU+2cxvxx3hhhtiPPwwFBeXcP/9sOmm4eWXWOPNlffb8lu/PGECdO0aY999YerU\nEpo29Su/isuxWIyysjKAP9rLSqlqtTegCJiesDwbKAzutwRmV7Ge+mz8+PFhh5BV2crv7bdVd9xR\ntUcP1WXLsrKLatlnl5tWr1bt3Vu1sFB19OiqXxfV/FIVtJ0btKm1LYncAvykqkNEpDdQoKobnHi0\nkoipyq+/wjXXuElQhw1zw7aa/Pbxx3D22VBU5PpW53PZrNY1bBEZCXQAtgQWA32BF4GngdbAPKCr\nqi6vZF1rsE1Sb77p/pN27Ai33upGATT55bffoH9/16f6ttvc1Yv5cGIxmVpfOKOqp6rqNqraSFVb\nqerDqrpUVY9Q1Taq2rGyxjofJNbRfFQX+R1xBEyf7i662X13eOqpurnYxj673DB+vBvaYP58+PRT\nNyVdKo11VPLLNLvS0YRus83cVZHPPgs33ADHHuv63Rp//fijm7qrRw8YOtR1/cznEkiqbCwRk1PW\nrHGjr916qxu+9fLLoVGjsKMymbJuHdx/vyuBdOsGAwe6L2zzZzano4mUuXPdJcizZ7u6ZqdOVteM\nuvfecxM4N2sG//2vG7jJVM4Gf8oC3+toYea3ww4wZowbj6RPHzjySFfrzhT77OrON99A9+5w8smu\nZ9D48ek31rmUX12yBtvktI4dYdo0N5TmEUe4yVUXLQo7KpOKpUtdWatdO9dVb/ZsOOUU+6WUDiuJ\nmMhYtsydlCwrg3PPhauvhs03DzsqU9GqVa7kccstcMIJrl7dsmXYUUWLlURM5DVv7ib+nTbNNd5t\n2sCgQfDLL2FHZsA11Pfc4z6XDz6ACRPcCUZrrDPHGuw0+F5Hy9X8ttvONQQffgiffw477wyDB7tG\nPFW5mlum1GV+K1fCf/4DO+0Er78Ozz3nRtjbdYPxOzPH98+vKtZgm8jaeWc3n9/48TBnjlu++mpY\nuDDsyPLDihWuB8+OO8Lbb7uTxKNHQ/v2YUfmL6thG298840rmTz2GJx0kht7e/fdw47KP19/7aaB\ne+QRNwZM797uakWTOVbDNt7bfnvXkHz+ORQWwuGHu5m0R42CtWvDji7aVN241Cec4CZXbtzYXUr+\nxBPWWNcla7DT4HsdLar5bbUVDBjgjrjPO89dObnDDq6Hyfffu9dENbdUZSq/H35wZY/ddoPzz3dd\nK7/5Bm6+2Z1LCIvvn19VrME23mrUyPX7ffddV1/97jt3wUbHjjB2bG5ODpwL1qyBV1+FE090PT5m\nzICHHoKZM+HCC6FJk7AjzF9WwzZ5ZeVKd2JsxAjX9axLF+ja1ZVONtoo7OjCs24dxGLw9NOuhLTT\nTnDmme4Lr1mzsKPLPzaWiDEVLFoEI0e6bmgzZsAxx7grKo85Bpo2DTu67Fu50jXSY8a4Rnq77dyX\nV9eu7spEE56snHQUkXki8qmITBGRSelsK4p8r6P5nF8sFqOwEHr1ciWTWbOgQwf303+bbdzYJUOG\nwCefQHl52NHWXGWfnSp89RXcfbcbwrZFC1eL3n579x5Mnuy6RUahsfb5bzOZdGvYCpSo6j6qul8m\nAoqSqVOnhh1CVvmcX8XcCgvdSbXXXnO17p493aD63bq5cZpPPtldbj1pEqxeHVLQNTB16lTKy13d\n+b773CwurVvDwQe7qbjOPBO+/db1n77mGteHPUp8/ttMJu1Z04G8Hcpl+XK/J9rxOb9kuTVrBp07\nuxu4Bvytt1zN+8EH4csv3cnL/feH4mLYYw/X3zvMMsrq1fDFFzB1qvtVMGrUcvr3d2OtHHKI6+LY\nv79rmH0YfMnnv81k0m2wFXhTRNYB96vqsAzEZExOadUKSkvdDdwEwh9/DBMnwrhx7sh79mx3JL7b\nbq7EsP32rrSw/fau9LDllm6g/to2lqtWuSs4FyxwXRMXLHBjhs+Z4/qdL1jg9lVc7EbH+9vf4M47\n3X6NP9JtsA9S1YUishUwVkRmq+qETAQWBfPmzQs7hKzyOb90cmva1NW7O3RY/9i6da4BnT3b9VP+\n5ht3tDtvHixZ4qbEWrXKHfEWFMDGG7uLTxo3dr1TVN021q1zF/msWuUu/Y7fysvdIErbbutq7Ntu\n60ocRx7put7tsAM0bLg+ntLSeV431j7/bSaTsV4iItIP+FVVb094zLqIGGNMLVTWS6TWR9gisglQ\nX1V/EZEmQEdgQHU7NMYYUzv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"text": [
""
]
}
],
"prompt_number": 19
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"min_beta = float(df[df['MSE']==df['MSE'].min()]['beta'])\n",
"df[df['MSE']==df['MSE'].min()]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"
\n",
" \n",
" \n",
" \n",
" beta \n",
" MSE \n",
" \n",
" \n",
" \n",
" \n",
" 365 \n",
" 0.65 \n",
" 5.000338 \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 20,
"text": [
" beta MSE\n",
"365 0.65 5.000338"
]
}
],
"prompt_number": 20
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"float(min_beta)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 21,
"text": [
"0.6499999999999222"
]
}
],
"prompt_number": 21
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Lets create the linear regression and see if we get the same answer"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Using scipy"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from scipy.stats import linregress"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 22
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"slope, intercept, rvalue, pvalue, stderr = linregress(heig['parent'], heig['child'])"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 23
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"slope"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 24,
"text": [
"0.64629058199363942"
]
}
],
"prompt_number": 24
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"MSE(slope)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 25,
"text": [
"5.0002937655516639"
]
}
],
"prompt_number": 25
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Using StatsModels"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import statsmodels.formula.api as sm"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 26
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"result = sm.ols(formula=\"child ~ parent\", data=heig).fit()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 27
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Some Basic Notation and Background"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We write $X_1, X_2, ... X_n$ to describe $n$ data points"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Uppercase $X$ for a random variable\n",
"* lowercase $x$ for a particular value\n",
"* greek letters for things we don't know"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Empirical Mean\n",
"\n",
"$\\hat{X} = \\dfrac{1}{n}\\sum\\limits_{i=1}^n X_i$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If we subtract the mean from all data points, we get data that has a mean of 0.\n",
"\n",
"$\\hat{X_i} = X_i - \\hat{X} = 0$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Remember the mean is the least squares solution for minimizing:\n",
" \n",
"$\\sum\\limits_{i=1}^n (X_i - \\mu)^2$\n",
"\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# The empirical standard deviation and variance"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$\\text{Variance: } s^2 = \\dfrac{1}{n-1}\\sum\\limits_{i = 1}^n {\\left( {X_i - \\bar X} \\right)^2 } $"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Normalization\n",
"\n",
"$Z_i = \\dfrac{X_i - \\bar x}{s}$\n",
"\n",
"* Normalizing gives an empiricial mean of zero and a empirical standard deviation of 0\n",
"* Its units are described in standard deviations from the mean\n",
"* A z value of 2 means the normalized observation is 2 standard deviations from the mean"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# The empirical covariance"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"of $n$ observations is ..\n",
"\n",
"$Cov(X, Y) = \\dfrac{1}{n-1}\\sum\\limits_{i=1}^n(X_i - \\hat X)(Y_i - \\hat Y) = \\dfrac{1}{n-1}\\left(\\sum\\limits_{i=1}^nX_iY_i - n\\hat X\\hat Y\\right)$\n",
"\n",
"* think of covariance as a function that takes two vectors as an input\n",
"* has the units of X and Y"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Correlation is:"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$ Cor(X, Y) = \\dfrac{Cov(X, Y)}{S_xS_y}$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Where\n",
"\n",
"* $S_x$ is the estimate of the standard deviation for the $X$ observations\n",
"* $S_y$ is the estimate of the standard deviation for the $Y$ observations\n",
"* Unit free, between -1 and 1"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$Cor(X, Y) = \\pm 1$ only when the $X$ or $Y$ observations fall perfectly on a posivite or negative sloped line"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$Cor(X, Y) = 0$ implies no linear relationship"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Least squares estimation of regression lines"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Let $Y_i$ be the $i^{th}$ child's height\n",
"* Let $X_i$ be the $i^{th}$ parents' average height\n",
"\n",
"Consider finding the best line\n",
"\n",
"Child's Height = $\\beta_0$ + Parent's Height $\\cdot \\beta_1$\n",
"\n",
"Use least squares\n",
"\n",
"\n",
"$\n",
"\\sum\\limits_{i=1}^n(Y_i - (\\beta_0 + \\beta_1X_i))^2 \n",
"$\n",
"- the difference between the actual and the predicted\n",
"\n",
"$\n",
"\\sum\\limits_{i=1}^n{\\big(Y_i - \\hat Y\\big)}^2 \n",
"$ - the difference between the actual and the predicted\n",
"\n",
"Oh how the fuck how do we do it?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Mean only regression"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So after a lot of stuff...\n",
"\n",
"$\n",
"\\hat\\beta_1 = \\dfrac{\\sum\\limits_{i=1}^n Y_iX_i}{\\sum\\limits_{i=1}^nX_i^2}\n",
"$\n",
"\n",
"When we restrict the line through the origin"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Figuring out the final forms we can use to get $\\beta_n$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"... lots of math... which can be summarized as\n",
"\n",
"$\\hat \\beta_1 = Cor(Y, X) \\dfrac{S_dY}{S_dX}$\n",
"\n",
"also stated as\n",
"\n",
"$\\dfrac{\\sum(X-\\bar X) \\sum (Y - \\bar Y)}{\\sum(X - \\bar X)^2}$\n",
"\n",
"and \n",
"\n",
"$\\hat \\beta_0 = \\bar Y - \\hat \\beta_1 \\bar X$\n",
"\n",
"And our regression line always travels through $(\\bar X, \\bar Y)$"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"heig = pd.DataFrame.from_csv('data/Galton.csv', index_col=None)\n",
"heig.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
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" \n",
" 4 \n",
" 61.7 \n",
" 64.0 \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 28,
"text": [
" child parent\n",
"0 61.7 70.5\n",
"1 61.7 68.5\n",
"2 61.7 65.5\n",
"3 61.7 64.5\n",
"4 61.7 64.0"
]
}
],
"prompt_number": 28
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"y = 'child'\n",
"x = 'parent'\n",
"\n",
"beta1 = heig[y].corr(heig[x]) * heig[y].std() / heig[x].std()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 29
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"beta0 = heig[y].mean() - beta1 * heig[x].mean()\n",
"beta0"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 30,
"text": [
"23.941530180421658"
]
}
],
"prompt_number": 30
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"beta1"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 31,
"text": [
"0.64629058199351186"
]
}
],
"prompt_number": 31
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"result = sm.ols(formula=\"child ~ parent\", data=heig).fit()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 32
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"result.params"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 33,
"text": [
"Intercept 23.941530\n",
"parent 0.646291\n",
"dtype: float64"
]
}
],
"prompt_number": 33
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Regression to the Mean"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$P(Y < x| X=x)$ gets bigger as $x$ heads to very large values\n",
"\n",
"$P(Y > x| X=x)$ gets bigger as $x$ heads to very small values"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Quiz"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### q1"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# q1 - what's a better way to do this?\n",
"x = [0.18, -1.54, 0.42, 0.95]\n",
"w = [2, 1, 3, 1]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 34
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Give the value of $\\mu$ that minimizes $\\sum\\limits_{i=1}^nw_i(x_i - \\mu)^2$"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df = pd.DataFrame([x, w]).T\n",
"df.columns = ['x', 'w']\n",
"df"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"
\n",
" \n",
" \n",
" \n",
" x \n",
" w \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" 0.18 \n",
" 2 \n",
" \n",
" \n",
" 1 \n",
" -1.54 \n",
" 1 \n",
" \n",
" \n",
" 2 \n",
" 0.42 \n",
" 3 \n",
" \n",
" \n",
" 3 \n",
" 0.95 \n",
" 1 \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 35,
"text": [
" x w\n",
"0 0.18 2\n",
"1 -1.54 1\n",
"2 0.42 3\n",
"3 0.95 1"
]
}
],
"prompt_number": 35
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"square = lambda x: x**2\n",
"f1 = lambda mu: (df['w'] * (df['x'] - mu).apply(square)).sum()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 36
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mus = np.arange(0, 1, .01)\n",
"f1(.18)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 37,
"text": [
"3.7241"
]
}
],
"prompt_number": 37
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mus = pd.DataFrame([(mu, f1(mu),) for mu in mus], columns = ['mu', 'fx'])"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 38
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"pd.DataFrame.plot(mus, x = 'mu', y='fx', title='Minimizing Mu');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
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22cxmmNkNpQisXKlvlkn5SFEuMikf2eUszO5eD3zL3bsD3wC+ZWaHFj2yMjV5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\n",
"text": [
""
]
}
],
"prompt_number": 39
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mus[mus['fx']==mus['fx'].min()]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"
\n",
" \n",
" \n",
" \n",
" mu \n",
" fx \n",
" \n",
" \n",
" \n",
" \n",
" 15 \n",
" 0.15 \n",
" 3.7166 \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 40,
"text": [
" mu fx\n",
"15 0.15 3.7166"
]
}
],
"prompt_number": 40
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# q2\n",
"x = [0.8, 0.47, 0.51, 0.73, 0.36, 0.58, 0.57, 0.85, 0.44, 0.42]\n",
"y = [1.39, 0.72, 1.55, 0.48, 1.19, -1.59, 1.23, -0.65, 1.49, 0.05]\n",
"df = pd.DataFrame([x, y]).T\n",
"df.columns = ['x', 'y']\n",
"df.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"
\n",
" \n",
" \n",
" \n",
" x \n",
" y \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" 0.80 \n",
" 1.39 \n",
" \n",
" \n",
" 1 \n",
" 0.47 \n",
" 0.72 \n",
" \n",
" \n",
" 2 \n",
" 0.51 \n",
" 1.55 \n",
" \n",
" \n",
" 3 \n",
" 0.73 \n",
" 0.48 \n",
" \n",
" \n",
" 4 \n",
" 0.36 \n",
" 1.19 \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 41,
"text": [
" x y\n",
"0 0.80 1.39\n",
"1 0.47 0.72\n",
"2 0.51 1.55\n",
"3 0.73 0.48\n",
"4 0.36 1.19"
]
}
],
"prompt_number": 41
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#result = sm.ols(formula=\"child ~ parent\", data=heig).fit()\n",
"# y intercept set to zero\n",
"result = sm.ols(formula=\"y ~ x - 1\", data=df).fit()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 42
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"result.summary()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stderr",
"text": [
"/Users/idris/.virtualenvs/regres/lib/python2.7/site-packages/scipy/stats/stats.py:1205: UserWarning: kurtosistest only valid for n>=20 ... continuing anyway, n=10\n",
" int(n))\n"
]
},
{
"html": [
"\n",
"OLS Regression Results \n",
"\n",
" Dep. Variable: y R-squared: 0.183 \n",
" \n",
"\n",
" Model: OLS Adj. R-squared: 0.092 \n",
" \n",
"\n",
" Method: Least Squares F-statistic: 2.018 \n",
" \n",
"\n",
" Date: Tue, 30 Sep 2014 Prob (F-statistic): 0.189 \n",
" \n",
"\n",
" Time: 15:48:14 Log-Likelihood: -14.561 \n",
" \n",
"\n",
" No. Observations: 10 AIC: 31.12 \n",
" \n",
"\n",
" Df Residuals: 9 BIC: 31.42 \n",
" \n",
"\n",
" Df Model: 1 \n",
" \n",
"
\n",
"\n",
"\n",
" coef std err t P>|t| [95.0% Conf. Int.] \n",
" \n",
"\n",
" x 0.8263 0.582 1.421 0.189 -0.490 2.142 \n",
" \n",
"
\n",
"\n",
"\n",
" Omnibus: 2.980 Durbin-Watson: 3.044 \n",
" \n",
"\n",
" Prob(Omnibus): 0.225 Jarque-Bera (JB): 1.581 \n",
" \n",
"\n",
" Skew: -0.959 Prob(JB): 0.454 \n",
" \n",
"\n",
" Kurtosis: 2.658 Cond. No. 1.00 \n",
" \n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 43,
"text": [
"\n",
"\"\"\"\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: y R-squared: 0.183\n",
"Model: OLS Adj. R-squared: 0.092\n",
"Method: Least Squares F-statistic: 2.018\n",
"Date: Tue, 30 Sep 2014 Prob (F-statistic): 0.189\n",
"Time: 15:48:14 Log-Likelihood: -14.561\n",
"No. Observations: 10 AIC: 31.12\n",
"Df Residuals: 9 BIC: 31.42\n",
"Df Model: 1 \n",
"==============================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"------------------------------------------------------------------------------\n",
"x 0.8263 0.582 1.421 0.189 -0.490 2.142\n",
"==============================================================================\n",
"Omnibus: 2.980 Durbin-Watson: 3.044\n",
"Prob(Omnibus): 0.225 Jarque-Bera (JB): 1.581\n",
"Skew: -0.959 Prob(JB): 0.454\n",
"Kurtosis: 2.658 Cond. No. 1.00\n",
"==============================================================================\n",
"\"\"\""
]
}
],
"prompt_number": 43
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## So that's the code way to do it. Let's do it symbolically too.\n",
"\n",
"$\\beta_1 = \\dfrac{\\sum(X_i - \\bar X)(Y_i - \\bar Y)}{\\sum(X_i - \\bar X)^2}$\n",
"\n",
"wait... that's close.\n",
"\n",
"But for a RTO (\"regression through origin\")\n",
"Remember that $\\bar X$ and $\\bar Y$ for a RTO are both $0$\n",
"\n",
"$\\beta_1 = \\dfrac{\\sum X_iY_i}{\\sum X_i^2}$"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = 'x'\n",
"y = 'y'\n",
"num = (df[x] * df[y]).sum()\n",
"den = (df[x]).apply(square).sum()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 44
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"num / den"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 45,
"text": [
"0.82625166087128599"
]
}
],
"prompt_number": 45
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### q3"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R -i x\n",
"require(dataset)\n",
"data(mtcars)\n",
"head(mtcars)\n",
"lm(mpg~wt, data=mtcars)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"Loading required package: dataset\n",
"\n",
"Call:\n",
"lm(formula = mpg ~ wt, data = mtcars)\n",
"\n",
"Coefficients:\n",
"(Intercept) wt \n",
" 37.285 -5.344 \n",
"\n"
]
}
],
"prompt_number": 46
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## q4 \n",
"\n",
"Consider data with an outcome (Y) and a predictor (X). The standard deviation of the predictor is one half that of the outcome. The correlation between the two variables is .5. What value would the slope coefficient for the regression model with Y as the outcome and X as the predictor?\n",
"\n",
"* $Cor(X, Y) = \\frac{1}{2}$\n",
"* $2 \\cdot S_d(X) = S_d(Y)$\n",
"* $\\hat \\beta_1 = Cor(Y, X) \\dfrac{S_dY}{S_dX}$\n",
"* $\\hat \\beta_1 = \\frac{1}{2} \\dfrac{2S_dY}{S_dX} = \\frac{1}{2}\\cdot\\frac{2}{1}$\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### q5"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Students were given two hard tests and scores were normalized to have empirical mean 0 and variance 1. The correlation between the scores on the two tests was 0.4. What would be the expected score on Quiz 2 for a student who had a normalized score of 1.5 on Quiz 1?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$Cor(q1, q2) = 0.4 $\n",
"\n",
"$ Z_{q1} = 1.5 $"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"1.5 *0.4 #???"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 47,
"text": [
"0.6000000000000001"
]
}
],
"prompt_number": 47
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### q6"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = [8.58, 10.46, 9.01, 9.64, 8.86]\n",
"s = pd.Series(x)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 48
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# normalized values\n",
"ns = (s - s.mean())/s.std()\n",
"ns"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 49,
"text": [
"0 -0.971866\n",
"1 1.531022\n",
"2 -0.399397\n",
"3 0.439337\n",
"4 -0.599095\n",
"dtype: float64"
]
}
],
"prompt_number": 49
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"ns.mean()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 50,
"text": [
"1.8873791418627661e-15"
]
}
],
"prompt_number": 50
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### q7"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"
\n",
" \n",
" \n",
" \n",
" x \n",
" y \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" 0.80 \n",
" 1.39 \n",
" \n",
" \n",
" 1 \n",
" 0.47 \n",
" 0.72 \n",
" \n",
" \n",
" 2 \n",
" 0.51 \n",
" 1.55 \n",
" \n",
" \n",
" 3 \n",
" 0.73 \n",
" 0.48 \n",
" \n",
" \n",
" 4 \n",
" 0.36 \n",
" 1.19 \n",
" \n",
" \n",
" 5 \n",
" 0.58 \n",
" -1.59 \n",
" \n",
" \n",
" 6 \n",
" 0.57 \n",
" 1.23 \n",
" \n",
" \n",
" 7 \n",
" 0.85 \n",
" -0.65 \n",
" \n",
" \n",
" 8 \n",
" 0.44 \n",
" 1.49 \n",
" \n",
" \n",
" 9 \n",
" 0.42 \n",
" 0.05 \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 51,
"text": [
" x y\n",
"0 0.80 1.39\n",
"1 0.47 0.72\n",
"2 0.51 1.55\n",
"3 0.73 0.48\n",
"4 0.36 1.19\n",
"5 0.58 -1.59\n",
"6 0.57 1.23\n",
"7 0.85 -0.65\n",
"8 0.44 1.49\n",
"9 0.42 0.05"
]
}
],
"prompt_number": 51
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"result = sm.ols(\"y ~ x\", data=df).fit()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 52
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"result.summary()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"OLS Regression Results \n",
"\n",
" Dep. Variable: y R-squared: 0.076 \n",
" \n",
"\n",
" Model: OLS Adj. R-squared: -0.039 \n",
" \n",
"\n",
" Method: Least Squares F-statistic: 0.6620 \n",
" \n",
"\n",
" Date: Tue, 30 Sep 2014 Prob (F-statistic): 0.439 \n",
" \n",
"\n",
" Time: 15:48:14 Log-Likelihood: -13.666 \n",
" \n",
"\n",
" No. Observations: 10 AIC: 31.33 \n",
" \n",
"\n",
" Df Residuals: 8 BIC: 31.94 \n",
" \n",
"\n",
" Df Model: 1 \n",
" \n",
"
\n",
"\n",
"\n",
" coef std err t P>|t| [95.0% Conf. Int.] \n",
" \n",
"\n",
" Intercept 1.5675 1.252 1.252 0.246 -1.320 4.455 \n",
" \n",
"\n",
" x -1.7128 2.105 -0.814 0.439 -6.568 3.142 \n",
" \n",
"
\n",
"\n",
"\n",
" Omnibus: 3.809 Durbin-Watson: 2.515 \n",
" \n",
"\n",
" Prob(Omnibus): 0.149 Jarque-Bera (JB): 1.534 \n",
" \n",
"\n",
" Skew: -0.956 Prob(JB): 0.464 \n",
" \n",
"\n",
" Kurtosis: 3.158 Cond. No. 8.37 \n",
" \n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 53,
"text": [
"\n",
"\"\"\"\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: y R-squared: 0.076\n",
"Model: OLS Adj. R-squared: -0.039\n",
"Method: Least Squares F-statistic: 0.6620\n",
"Date: Tue, 30 Sep 2014 Prob (F-statistic): 0.439\n",
"Time: 15:48:14 Log-Likelihood: -13.666\n",
"No. Observations: 10 AIC: 31.33\n",
"Df Residuals: 8 BIC: 31.94\n",
"Df Model: 1 \n",
"==============================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"------------------------------------------------------------------------------\n",
"Intercept 1.5675 1.252 1.252 0.246 -1.320 4.455\n",
"x -1.7128 2.105 -0.814 0.439 -6.568 3.142\n",
"==============================================================================\n",
"Omnibus: 3.809 Durbin-Watson: 2.515\n",
"Prob(Omnibus): 0.149 Jarque-Bera (JB): 1.534\n",
"Skew: -0.956 Prob(JB): 0.464\n",
"Kurtosis: 3.158 Cond. No. 8.37\n",
"==============================================================================\n",
"\"\"\""
]
}
],
"prompt_number": 53
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### q9"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"What value minimizes the sum of the squared distances between these points and itself?\n",
"\n",
"By definition: see [this](#experiment)"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df['x'].mean()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 54,
"text": [
"0.57299999999999995"
]
}
],
"prompt_number": 54
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### q10"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Consider taking the slope having fit Y as the outcome and X as the predictor, \u03b21 and the slope from fitting X as the outcome and Y as the predictor, \u03b31, and dividing the two as \u03b21/\u03b31. What is this ratio always equal to"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"
\n",
" \n",
" \n",
" \n",
" x \n",
" y \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" 0.80 \n",
" 1.39 \n",
" \n",
" \n",
" 1 \n",
" 0.47 \n",
" 0.72 \n",
" \n",
" \n",
" 2 \n",
" 0.51 \n",
" 1.55 \n",
" \n",
" \n",
" 3 \n",
" 0.73 \n",
" 0.48 \n",
" \n",
" \n",
" 4 \n",
" 0.36 \n",
" 1.19 \n",
" \n",
" \n",
" 5 \n",
" 0.58 \n",
" -1.59 \n",
" \n",
" \n",
" 6 \n",
" 0.57 \n",
" 1.23 \n",
" \n",
" \n",
" 7 \n",
" 0.85 \n",
" -0.65 \n",
" \n",
" \n",
" 8 \n",
" 0.44 \n",
" 1.49 \n",
" \n",
" \n",
" 9 \n",
" 0.42 \n",
" 0.05 \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 55,
"text": [
" x y\n",
"0 0.80 1.39\n",
"1 0.47 0.72\n",
"2 0.51 1.55\n",
"3 0.73 0.48\n",
"4 0.36 1.19\n",
"5 0.58 -1.59\n",
"6 0.57 1.23\n",
"7 0.85 -0.65\n",
"8 0.44 1.49\n",
"9 0.42 0.05"
]
}
],
"prompt_number": 55
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"r1 = sm.ols(\"x~y\", data=df).fit()\n",
"r2 = sm.ols(\"y~x\", data=df).fit()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 56
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"r2.params.x / r1.params.y"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 57,
"text": [
"38.390772016849851"
]
}
],
"prompt_number": 57
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df['y'].var() / df['x'].var()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 58,
"text": [
"38.390772016849652"
]
}
],
"prompt_number": 58
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$\\beta_1 = Cor(X, Y)\\dfrac{S_y}{S_X}$\n",
"\n",
"$\\gamma_1 = Cor(X, Y)\\dfrac{S_X}{S_Y}$\n",
"\n",
"$\\dfrac{\\beta_1}{\\gamma_1} = \\dfrac{Cor(X, Y)\\dfrac{S_y}{S_X}}{Cor(X, Y)\\dfrac{S_X}{S_Y}}$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$\\dfrac{S_Y}{S_X}\\cdot\\dfrac{S_Y}{S_X} = \\dfrac{S_Y^2}{S_X^2} = \\dfrac{Var(Y)}{Var(X)}$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Week 2\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" \n",
"## Statistical linear regression models"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Basic regression model with additive Gaussian errors"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Least squares is an estimation tool, how do we do inference?\n",
"* Develop a probabilistic model for linear regression\n",
"* $\\epsilon$ is the error\n",
"\n",
"$Y_i = \\beta_0 + \\beta_1X_i + \\epsilon_i$\n",
"\n",
"slope intercept line with error term"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here the $\\epsilon_i$ are assumed iid $N(0, \\sigma^2)$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$\n",
"E[Y_i | X_i = x_i] = \\mu_i = \\beta_0 + \\beta_1x_i\n",
"$\n",
"\n",
"The expected value of $Y_i$ given $x_i$ is the regression equation. You take the expected value of the equation above and the $E[\\epsilon_i]=0$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$\n",
"Var(Y_i | X_i = x_i) = \\sigma^2\n",
"$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Likelihood\n",
"\n",
"* see the statistical inference class\n",
"* The least squares estimate for $\\mu_i$ is exactly the maximum likelihood estimate"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Recap\n",
"\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Interpreting regression coefficients"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$\\beta_0$ is the expected value of the response when the predictor is 0"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$E[Y|X=0] = \\beta_0 + \\beta_1 \\cdot 0 = \\beta_0$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This isn't always interesting, when $X=0$ is impossible or far outside of the range of possible values"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" You can shift the data by $a$, which changes the intercept but not the slope. In this way you can make the intercept interesting"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$\\beta_1$ is the expected change in response for a 1 unit change in the predictor"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Multiplication of $X$ by a factor of $a$ results in dividing the coefficient by a factor of $a$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Using the regression coefficients for prediction"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$\\hat Y = \\hat \\beta_0 + \\hat \\beta_1X$\n",
"\n",
"* Why are these $\\hat \\beta$ instead of just $\\beta$?\n",
"* Because the $\\beta$ values are just our estimations, specifically our least squares estimation\n",
"\n",
" \n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Statistical Regression Models Examples"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R -o diamond\n",
"require(UsingR)\n",
"require(ggplot2)\n",
"data(diamond)\n",
"g <- ggplot(diamond, aes(carat, price)) + geom_point() + theme_bw()\n",
"g <- g + geom_smooth(method=lm, se=FALSE)\n",
"g\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"Loading required package: UsingR\n",
"Loading required package: MASS\n",
"Loading required package: HistData\n",
"Loading required package: Hmisc\n",
"Loading required package: grid\n",
"Loading required package: lattice\n",
"Loading required package: survival\n",
"Loading required package: splines\n",
"Loading required package: Formula\n",
"\n",
"Attaching package: \u2018Hmisc\u2019\n",
"\n",
"The following object is masked from \u2018package:base\u2019:\n",
"\n",
" format.pval, round.POSIXt, trunc.POSIXt, units\n",
"\n",
"Loading required package: quantreg\n",
"Loading required package: SparseM\n",
"\n",
"Attaching package: \u2018SparseM\u2019\n",
"\n",
"The following object is masked from \u2018package:base\u2019:\n",
"\n",
" backsolve\n",
"\n",
"\n",
"Attaching package: \u2018quantreg\u2019\n",
"\n",
"The following object is masked from \u2018package:Hmisc\u2019:\n",
"\n",
" latex\n",
"\n",
"The following object is masked from \u2018package:survival\u2019:\n",
"\n",
" untangle.specials\n",
"\n",
"\n",
"Attaching package: \u2018UsingR\u2019\n",
"\n",
"The following object is masked from \u2018package:survival\u2019:\n",
"\n",
" cancer\n",
"\n",
"The following object is masked from \u2018package:ggplot2\u2019:\n",
"\n",
" movies\n",
"\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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wk7flC/6FnUiMVvSLZYw4wsomaBh8DCsRF1dasWKFTj31VO3atcvJ5bffftOo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\nDKsSjY++IwAAAABJRU5ErkJggg==\n"
}
],
"prompt_number": 59
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"formula = \"price ~ carat\"\n",
"r1 = sm.ols(formula, data=diamond).fit()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 60
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"r1.summary()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"OLS Regression Results \n",
"\n",
" Dep. Variable: price R-squared: 0.978 \n",
" \n",
"\n",
" Model: OLS Adj. R-squared: 0.978 \n",
" \n",
"\n",
" Method: Least Squares F-statistic: 2070. \n",
" \n",
"\n",
" Date: Tue, 30 Sep 2014 Prob (F-statistic): 6.75e-40 \n",
" \n",
"\n",
" Time: 15:48:16 Log-Likelihood: -233.20 \n",
" \n",
"\n",
" No. Observations: 48 AIC: 470.4 \n",
" \n",
"\n",
" Df Residuals: 46 BIC: 474.1 \n",
" \n",
"\n",
" Df Model: 1 \n",
" \n",
"
\n",
"\n",
"\n",
" coef std err t P>|t| [95.0% Conf. Int.] \n",
" \n",
"\n",
" Intercept -259.6259 17.319 -14.991 0.000 -294.487 -224.765 \n",
" \n",
"\n",
" carat 3721.0249 81.786 45.497 0.000 3556.398 3885.651 \n",
" \n",
"
\n",
"\n",
"\n",
" Omnibus: 0.739 Durbin-Watson: 1.994 \n",
" \n",
"\n",
" Prob(Omnibus): 0.691 Jarque-Bera (JB): 0.181 \n",
" \n",
"\n",
" Skew: 0.056 Prob(JB): 0.913 \n",
" \n",
"\n",
" Kurtosis: 3.280 Cond. No. 18.5 \n",
" \n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 61,
"text": [
"\n",
"\"\"\"\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: price R-squared: 0.978\n",
"Model: OLS Adj. R-squared: 0.978\n",
"Method: Least Squares F-statistic: 2070.\n",
"Date: Tue, 30 Sep 2014 Prob (F-statistic): 6.75e-40\n",
"Time: 15:48:16 Log-Likelihood: -233.20\n",
"No. Observations: 48 AIC: 470.4\n",
"Df Residuals: 46 BIC: 474.1\n",
"Df Model: 1 \n",
"==============================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"------------------------------------------------------------------------------\n",
"Intercept -259.6259 17.319 -14.991 0.000 -294.487 -224.765\n",
"carat 3721.0249 81.786 45.497 0.000 3556.398 3885.651\n",
"==============================================================================\n",
"Omnibus: 0.739 Durbin-Watson: 1.994\n",
"Prob(Omnibus): 0.691 Jarque-Bera (JB): 0.181\n",
"Skew: 0.056 Prob(JB): 0.913\n",
"Kurtosis: 3.280 Cond. No. 18.5\n",
"==============================================================================\n",
"\"\"\""
]
}
],
"prompt_number": 61
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# same formula, but subtracting out the carat mean to get a usable intercept values\n",
"f = \"price ~ I(carat - carat.mean())\"\n",
"r2 = sm.ols(f, data=diamond).fit()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 62
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# note that the slope is the same\n",
"print(r1.params)\n",
"print(r2.params)\n",
"print(diamond.price.mean())"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Intercept -259.625907\n",
"carat 3721.024852\n",
"dtype: float64\n",
"Intercept 500.083333\n",
"I(carat - carat.mean()) 3721.024852\n",
"dtype: float64\n",
"500.083333333\n"
]
}
],
"prompt_number": 63
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$500 (the intercept) is the expected price for the average sized diamond of the data.\n",
"\n",
"And the intercept is exactly the mean of the prices"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"diamond.price.mean()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 64,
"text": [
"500.08333333333331"
]
}
],
"prompt_number": 64
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Changing Scale"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# A one carat increase in diamond is pretty big.\n",
"f = \"price ~ I(carat *10)\"\n",
"r3 = sm.ols(f, data=diamond).fit()\n",
"r3.params"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 65,
"text": [
"Intercept -259.625907\n",
"I(carat * 10) 372.102485\n",
"dtype: float64"
]
}
],
"prompt_number": 65
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# And the slope is 1/coef we mutliplied the regressor by"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 66
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df = pd.DataFrame([0.16, 0.27, 0.34], columns=['carat'])\n",
"df['price'] = r3.predict(df)\n",
"df"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"
\n",
" \n",
" \n",
" \n",
" carat \n",
" price \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" 0.16 \n",
" 335.738069 \n",
" \n",
" \n",
" 1 \n",
" 0.27 \n",
" 745.050803 \n",
" \n",
" \n",
" 2 \n",
" 0.34 \n",
" 1005.522542 \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 67,
"text": [
" carat price\n",
"0 0.16 335.738069\n",
"1 0.27 745.050803\n",
"2 0.34 1005.522542"
]
}
],
"prompt_number": 67
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"diamond['price_predict'] = r3.predict(diamond)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 68
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R -i diamond\n",
"g <- ggplot(diamond, aes(carat, price)) + geom_point(color='green')\n",
"g <- g + geom_line(data=diamond, aes(carat, price_predict), colour='blue', linetype=2) \n",
"g <- g + geom_point(data=diamond, aes(carat, price_predict), colour='red', shape=3) \n",
"g + theme_bw()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
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TTwQQQCANApMnS+eeKx12WPWJhxSKWqDieNTMgIwQgAPS0FQTAQQQSLXAk09KQ4ZIU6ZI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\nh7/4UiVj73QM7zQvn32WDCfrIoAAAgggEJtA4AO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}
],
"prompt_number": 69
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# green dots - actual observations\n",
"# blue dashed line - predictions\n",
"# red dashes - places where we made predictions. Note that these are the same x_i values where we have observed points"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 70
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Residuals and residual variation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$\\hat Y_i = \\hat \\beta_0 + \\hat \\beta_1X_i$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$e_i = Y_i - \\hat Y_i$ which is the vertical distance between the observed data point and the regression line\n",
"\n",
"$e_i \\neq \\epsilon_i$. \n",
"\n",
"$e_i$ is the observed error, not the true error which we don't get to know"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Least squares minimizes $\\sum\\limits_{i=1}^ne_i^2$\n",
"\n",
"The $e_i$ can be thought of as the estimates of the $\\epsilon_i$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Properties of the residuals\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Useful for investigating poor model fit\n",
"* Residuals can be thought of as the outcome $Y$ with the linear association of the predictor $X$ removed\n",
"* residual variation is the variation after removing the systematic variation\n",
"* residual plots highlight poor model fit"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R -o diamond\n",
"data(diamond)\n",
"y <- diamond$price\n",
"x <- diamond$carat\n",
"n <- length(y)\n",
"fit <- lm(y~x)\n",
"e <- resid(fit)\n",
"yhat <- predict(fit)\n",
"max(abs(e - (y-yhat)))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"[1] 9.485746e-13\n"
]
}
],
"prompt_number": 71
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"diamond\n",
"x = diamond.carat\n",
"y = diamond.price\n",
"results = sm.ols(\"price ~ carat\", data=diamond).fit()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 72
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"e = results.resid"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 73
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"yhat = results.predict()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 74
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df = pd.DataFrame([e, y - yhat]).T\n",
"df.columns = ['e', 'y - yhat']"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 75
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
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" \n",
" 3 \n",
" -85.158566 \n",
" -85.158566 \n",
" \n",
" \n",
" 4 \n",
" -28.630306 \n",
" -28.630306 \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 76,
"text": [
" e y - yhat\n",
"0 -17.948318 -17.948318\n",
"1 -7.738069 -7.738069\n",
"2 -22.948318 -22.948318\n",
"3 -85.158566 -85.158566\n",
"4 -28.630306 -28.630306"
]
}
],
"prompt_number": 76
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"(df.e - df['y - yhat']).abs().max()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 77,
"text": [
"0.0"
]
}
],
"prompt_number": 77
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from statsmodels.api import graphics"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 78
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### What we're looking for is a pattern in the residuals. A pattern indicates our model is missing something"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"See [this](http://statsmodels.sourceforge.net/devel/examples/notebooks/generated/example_regression_plots.html) for more details on plotting regressions in statsmodels"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig, ax = plt.subplots(figsize=(12, 8))\n",
"fig = graphics.plot_fit(results, \"carat\", ax=ax)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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HR6FAe78gXgTaGxvpKBRcJUU6CEO4JEkZuvTSS2tdQsX0D+IbMYBLL4YhXJKk\nDN1+++21LqGi+oL4+ZMnG8ClF8EQLkmShiWXyzF1xgwDuPQiGMIlSZKkjBnCJUmSpIwZwiVJkqSM\nja91AZIk1VI+38Xy5QV6e8czYcIu2tqaaGmZWeuyJNU5Q7gkaczK57tYuHAtPT0de4/19LQDjPog\nXiwW2bJhA8Vi0RsmpRHIdhRJ0pi1fHlhQAAH6OnpoLNzXY0qqoxisUh7UxN3bNtGe1MTxeLgfS1H\nt3nz5tW6BGnYDOGSpDGrt3foXwjv3Dku40oqpy+Ad3R3Mw3o6O6uuyA+f/78WpcgDZshXJI0Zk2Y\nsGvI4xMn7s64ksroH8D7GlBy1GcQl0Y7Q7gkacxqa2uioaF9wLGGhitpbT27RhUNT/uCBSzqF8D7\n5IBF3d20L1hQg6okDcUbMyVJY1bfzZednUvYuXMcEyfuprX1nFF7U2bHihUvmAkHKALXNjbSsWJF\njSqTNFiklGpdQ0VERKqXzyJJql+TJ09m27ZtVbv+4JaUItDe2EhHoVDVVVJmz57NmjVrqnZ9aaSI\nCFJKMdzr2I4iSRJw0kkn1bqEisjlcnQUCrQ3NrKRbAK4pBfPdhRJkoDNmzfXuoSK6QviZ516KncZ\nwKURyZlwSZLqUC6XY+qMGQZwaYQyhEuSVGfy+S6amxdz771H0ty8mHy+q9YlSRrEdhRJkupIPt/F\nwoVr9+4EWihAT09pGcbRuuqLVI+cCZckqY4sX17YG8D79PR00Nm5rkYVSRqKIVySpIxs3LiRY379\nazZu3Fi1MXp7h/4l986d46o2pqQXzxAuSVIGNm7cyGVvfjOFlLjszW+uWhCfMGHXkMcnTtxdlfH6\nzJs3r6rXl+qNIVySpCrrC+Bff/ZZpgFff/bZqgXxtrYmGhraBxxraLiS1tazKz5Wf/Pnz6/q9aV6\n446ZkiSxdxe8il+3fwAfvJX8BydN4rqHHmLatGkVHTOf76Kzcx0bNjzMjBnTaW0925sypQqp1I6Z\nhnBJkqheCP+j44/n69u2MVTM3gh8cPJk/u/WrRUfF9xKXqoGt62XJGkU+Pp993HZpEkUBx0vApdN\nmsTX77uvFmVJqjFDuCRJVTRt2jSue+ghPtgviFezFUXS6GAIlySpyqZNm8b7l3+VOUeMZyMw54jx\nvH/5Vw3g0hhmCJckqcry+S6uvvrH3L3nUd7DZO7e8yhXX/1jt5OXxjBDuCRJVbZvF8tp/JytwDR3\nsZTGOENIaN2wAAAgAElEQVS4JElV5i6WkgYzhEuSVGW12sVS0shlCJckqcpqtYulpJHLEC5JGtPy\n+S6amxcDZ9DcvLgqN0u2tMxk2bJmmpuXMH782TQ3L2HZsnPcxVIaw9wxU5I0ZuXzXVx88S1s3fo0\np3A7P2UOxx9/DDfd9OGqBeTJkyezbdu2qlx7MHfMlCrPHTMlSRqmJUu+xtatT3Mmt7MWOJPb2br1\naZYs+VqtS6uIefPm1boESfvhTLgkacx62ctO5x2/+wG3AzlKO1nOAX700nfzzDPfr8qYWc6ES6o8\nZ8IlSRqGfD4/IIBT/vftwDt+9wPy+XztipNU95wJlySNSW+I4E5gqI3jNwLnAI9U8O+VfL6L5csL\n3H33jzjzzHfQ1tbkjZnSKFSpmfChdw+QJKnO/e/vfpeL3/veATPhUGpJubj8eqXk810sXLi2vGsm\nFArQ01NastAgLo1NtqNIksaklpYWPvnd7zKHUvCGfT3hn/zud2lpaanYWPu2rd/Hbeulsc0QLkka\ns1paWnj3Z65mDqUWlDnAuz9zdUUDOLhtvaQXMoRLkl6Us8+un10e8/ku/vEfd3A336UZuJvv8o//\nuKPiG/a4bb2kwQzhkqQXpaur8jtK1sq+NpEWfkoCWqrSJuK29ZIG88ZMSdKYlVWbSN/Nl52dS7jr\nrh9y1lnvpLXVbeulscwQLkkas7JsE2lpmUlLy0wmT57MnXd6Q6Y01hnCJUljVltbEz/+8UVs3TqF\n0l+Juzj++F/Q2rqgxpVJqneGcEnSGPdy4Kp+zz9Zq0IkjSHemClJGrOWLy+wdev/HnBs69b/7frd\nkqrOEC5JGrNqsX73nDlzqnZtSaOHIVySNGbVYv3u66+/vmrXljR6GMIlSWOW63dLqpVIKdW6hoqI\niFQvn0WSRrIJEybQ29tb6zIqJp/vorNzHWvXfp/m5tNpbT3b9bsl7VdEkFKKYV+nXoKrIVySslFv\nIbxP+S/WWpchaYSrVAg/pHaUiHhtRLyn/HhSRBwz3IElSZKkseqgITwiPgZ8A/hK+dCJwD9VsyhJ\nkiSpnh3KTPilwLuBpwFSSo8Cr65mUZIkSVI9O5QQ3ptS2tv8FxHjAZvmJEmSpMN0KCH8nohoByZF\nxNmUWlPWVLcsSZIkqX4ddHWUiBgHXAQ0lQ+tBW4aaUuRuDqKJGXD1VEkjWWZLVEYES8FdqaUdpef\njwMmpJSePexBI14B3AS8iVJry0eAnwKrgdcAm4APpJR+Wz7/CuCjwG6gLaVUGOKahnBJyoAhXNJY\nluUShXcDR/V7Pgn4l2GOuwz455TSqcB/Af4TuBxYl1J6PXBX+TkRMR24EJgOnAPcEBHu9ClJkqRR\n61DC7ISU0jN9T1JKOygF8cMSES8HTk8pfbV8vV0ppaeA9wG3lE+7BTiv/PhcYFVK6fmU0ibgZ8Db\nD3d8SdLhe/DBBzn597/nwQcfrHUpkjSqHUoI/11E/Le+JxHRCDw3jDGnAb+OiL+PiH+PiP9TbnmZ\nnFLaVj5nGzC5/PgEYHO/928Gpg5jfEnSYfj4x6/gk6edRgH45Gmn8fGPX1HrkirqxBNPrHUJksaQ\nQwnhfwHcFhE/iIgfUOrbbh3GmOOB/wrckFL6r8DvKLee9Ck3dx+oMc+mPUnK0Mc/fgU/vfEa7qA0\nk3IH8NMbr6mrIP7EE0/UugRJY8j4g52QUtoQEacCb6AUfh9JKT0/jDE3A5tTShvKz28HrgC2RsTx\nKaWtETEF+FX59S3ASf3ef2L52AssXbp07+NZs2Yxa9asYZQpSYJSC0pfAM+Vj+UoBfHzb7yGB/+/\nC3nb295WuwIlqYrWr1/P+vXrK37d/a6OEhFnpZTuiojzKYXvvrtAE0BK6ZuHPWhEF3BxSunRiFjK\nvh7z7Sml/xkRlwOvSCldXr4xcyWlPvCplG4K/YPBS6G4OookVcdbJk7kO729TBvitY3A+yZM4D92\n7sy6LEmqiUqtjnKgmfCZlFYpmc3Q7R+HHcIptbP8Y0QcCfRQWqJwHKW2l4soL1EIkFJ6OCJuAx4G\ndgGXmLYlKTv/8MMfctFppw2YCQcoUtpE4h9++MPaFCZJo9gB1wkvLwV4QUppdXYlHR5nwiWpevr3\nhOcoBfDzgVM+djlf+crVtS1OkjKUyTrhKaU9wKeHO4gkaXT7yleu5pSPXc75lFpQDOCSNDyHsmPm\nNcBvKK2K8ru+4ymlJ6tb2ovjTLikkWblypXMnz+/1mVU1IMPPsgFp53GNx54wJsxJY1JWW5bv4kh\nesJTSkPdo1MzhnBJI83s2bNZs2ZNrcuouHrdtl6SDkUWN2b2ORW4FHg3sAf4AfC3wx1YkiRJGqsO\nJYR/DXgaWEZpmcL55WMXVLEuSZIkqW4dSgh/U0pper/nd0fEw9UqSJIkSap3h7Jt/b9HxLv6nkTE\nO4F/q15JkiRJUn07lJnwRuD/RsQTlG7QPBl4JCL+A0gppf9SzQIlSZKkenMoIfycqlchSZIkjSEH\nDeEppU0Z1CFJkiSNGYfSEy5JEvl8F83Ni/n97/+Q5ubF5PNdtS5JkkatQ2lHkSSNcfl8FwsXrqWn\npwOAQgF6etoBaGmZWcvSJGlUciZcknRQy5cX9gbwPj09HXR2rqtRRZI0uhnCJUkH1ds79C9Od+4c\nl3ElklQfDOGSxpyVK1fWuoRRZ8KEXUMenzhxd8aVSFJ9MIRLGnNWrVpV6xJGnba2Jhoa2gcca2i4\nktbWs2tUkSSNbt6YKUk6qL6bLzs7l7B27Q9obn43ra3neFOmJB0mQ7gk6ZC0tMykpWUmEyZM4M47\n/7XW5UjSqGY7iiRJkpQxQ7gkSZKUMUO4JEmSlDFDuCRVQbFYZMuGDRSLxVqXUnEzZ3ozpiQNlyFc\nkiqsWCzS3tTEHdu20d7UVHdBfN06d8mUpOEyhEtSBfUF8I7ubqYBHd3ddRnEJUnDYwiXpArpH8Bz\n5WM5DOKSpBcyhEtShbQvWMCifgG8Tw5Y1N1N+4IFNahKkjQSGcIlqUI6Vqzg2sZGBs93F4FrGxvp\nWLGiBlVJkkYiQ7gkVUgul6OjUKC9XxAvAu2NjXQUCuRyg+fIJUljlSFc0oiwcuXKWpdQEf2D+EYM\n4JKkoRnCJY0Iq1atqnUJFdMXxM+fPNkALkkakiFckqogl8sxdcYMA7gkaUiGcEljRj7fRXPzYu69\n90iamxeTz3fVuiRJ0hg1vtYFSFIW8vkuFi5cS09PBwCFAvT0tAPQ0uI27JKkbDkTLmlMWL68sDeA\n9+np6aCz0y3YJUnZM4RLGhN6e4f+xd/OneMyrkSSJEO4pBrLqk97woRd5UdFTuBcKK/kPXHi7qqM\nJ0nSgdgTLqlmsuzTbmtr4tFHP8krN32f2+jmAzTxm9e+m9bWP63oOFD6XMuXF+juLn2xaGtrsu9c\nkjRApJRqXUNFRESql88ijRXNzYspFK4a4vgS7rzzCxUdq1gscunb38X1P3uEHKV58Ev/4A1cf/99\nFV1GcPAXC4CGhnaWLWs2iEtSHYgIUkox3OvYjiKpZrLq0y4Wi7Q3Ne0N4AA54PqfPUJ7UxPFYvFA\nb39RvAFUknQoDOGSamZfn/ZAle7Tbl+wgEXd3Qye784Bi7q7aV+woGJjeQOoJOlQGMIl1UxbWxMN\nDe0DjjU0XElr69kVHadjxQqubWxk8Hx3Ebi2sZGOFSsqNlZWXywkSaObIVxSzbS0zGTZsmaam5dw\n7LHn09y8hGXLzql473Qul6OjUKC9XxAvAu2NjXQUChXtCc/qi4UkaXTzxkxJL9C3usddd/2Qs856\nZyare8yePZs1a9ZUdYy+3vBF3d2lGfAKB/A++XwXnZ3r2LDhYWbMmE5r69nelClJdaJSN2YawiUN\nUKvVPbII4VAK4medeip3/eQnVQng/WX1mSRJ2alUCHedcEkDlFb3aAYWU/pfxC56eprp7FxXF7O5\nuVyOqTNmVD2AS5J0IIZwSQNs2fJrYC3Qf5m9djZv/k2NKpIkqf54Y6akAbZu/S0DAzhAB1u3PlWL\nciRJqkuGcEkDTJkyZT/Hj8+4EkmS6pchXNIAJ5zwsiGPT516dNXGLBaLbNmwoaI7V0qSNJIZwiUN\nkPU6133LBt6xbVvFt5CvtXnz5tW6BEnSCGUIlzRA/w10YFbVNtCBfQG8o7ubaUBHd3ddBfH58+fX\nugRJ0ghlCJc0pL5196u1/n7/AN63WGCO+gvikiQNxSUKJQ0weLOeQgF6ekrtKZWcDW9fsIBF/QJ4\nnxywqLub9gULuOHb367YeJIkjSTOhEsaYOBmPUuBxXs366mkjhUruLaxkcHz3UUobSm/YkVFx5Mk\naSQxhEsaYN9mPVdRCuFXAWvZvPlXFR0nl8vRUSjQ3i+IF4H2xkY6CgV3tJQk1TVDuKQBstysp38Q\n34gBXJI0dhjCpVFm4sSJVb1+1pv19AXx8ydPNoBLksYMQ7g0yvT29lb1+rXYrCeXyzF1xgwDuCRp\nzDCESxog6816JEkai1yiUNIAfcsQdnYuYe3a79PcfDqtrdXZrEeSpLHKmXBJQ6r2Zj2SJI1lzoRL\nGiCrzXokSRrLnAmXNEBps54OYDWnEMBqeno6Kr5ZjyRJY5khXNIAvb3jgdWcyVzWAmcyF1jNzp3j\nalxZ5cybN6/WJUiSxjhDuKQBtm9/gDOZy+3ANOB2SkF8+/YHa1xZ5cyfP7/WJUiSxjhDuKS9Vq9e\nzasf+g63A30rducoBfFXP/RtVq9eXbviJEmqIzUL4RExLiIeiIg15efHRsS6iHg0IgoR8Yp+514R\nET+NiP+MiKZa1SzVu8/MnctN7AvgfXLATeXXJUnS8NVyJnwh8DDQt/7Z5cC6lNLrgbvKz4mI6cCF\nwHTgHOCGiHAGX6qCz996KxcDxUHHi8DF5dclSdLw1STMRsSJwJ9QmlyL8uH3AbeUH98CnFd+fC6w\nKqX0fEppE/Az4O3ZVSuNHRdeeCEfu/VW5rAviBeBOcDHbr2VCy+8sHbFSZJUR2o1o/xlYBGwp9+x\nySmlbeXH24DJ5ccnAJv7nbcZmFr1CqUxqn8Q34gBXJKkash8s56IeC/wq5TSAxExa6hzUkopIg60\nTd+Qry1dunTv41mzZjFr1pCXl6riZS97Gc8880yty6iIvsDdPHcuXzCAS5LGsPXr17N+/fqKXzey\n3pI6Ir4IfAjYBUwEjgG+CcwAZqWUtkbEFOBfU0pvjIjLAVJK15Tffyfw2ZTSjwZdN7m9tmopIjLZ\n4j2rcbIea/bs2axZsyaTsSRJOlzlvxvj4GceWObtKCmlK1NKJ6WUpgFzgbtTSh8CvgN8uHzah4Fv\nlR9/B5gbEUdGxDTgFOD+rOuWJEmSKiXzdpQh9E2zXQPcFhEXAZuADwCklB6OiNsoraSyC7jEKW9J\nkiSNZjUN4Smle4B7yo+fBN6zn/O+CHwxw9IkSZKkqnG9bUmSJCljhnBpFFm+fDmnlP9db+bNm1fr\nEiRJykzmq6NUi6ujqNaqvZLI8uXL+fbChdxEaffKc5cto62trWrjQbaro0iSNBpUanWUkXBjpqSD\n6AvgtwM54HZgzsKFAFUP4pIkqfJsR5FGuMEBHPYF8W8vXFiXrSmSJNU721GkCqlW68YbIrgTmDbE\naxuBc4BHqvSzbzuKJEkDjdrNeiS9OJcuW8bFQHHQ8SKl3vBLly3LvihJkjQshnBphGtra+PcZcuY\nw74gXgTmkM3NmZIkqfIM4aprxx13XK1LqIj+QXwjBnBJkkY7Q7jq2pNPPlnrEirmySfHc99Rb6UZ\nuO+ot/Lkky5uJEnSaGUIl0aBpUtv4KqrHuC55x7kpySee+5BrrrqAZYuvaHWpUmSpMPg6iiqa1mu\n7lHNsY455jx27PjWC44fffR5PP30C49XiqujSJI0kKujSCNEPt9Fc/Ni4AyamxeTz3dVfIxnnhm6\n9WR/xyVJ0sjm3+DSMOTzXSxcuJaeng4ACgXo6WkHoKVlZsXGSem5/RzfWbExJElSdpwJl4Zh+fIC\nPT3NwGJgKbCYnp5mOjvXVXikZ4D2QceuBHZUeBxJkpQFZ8KlYdiy5dfAWuB1nMLF/JSbgLVs3vyb\nCo80EXgcWAKMA3aXn0+s8DgDHXvssVW9viRJY5Uz4dIw/PznW4HXcSYXsxY4k4uB15WPV85RR40H\n/nzQ0Y9x1FEvqeg4g23fvr2q15ckaawyhEvD8NxzmziTi7kdmAbcTimIP/fcpoqO8+lPtxCxAvgC\npbaXLxCxgk9/+k8qOo4kScqGIVw6TDfffDNn8mNuB3LlYzn6gviPufnmmys21tKll/CZzzRy3HFz\ngfM47ri5fOYzjSxdeknFxpAkSdlxnXDVtWquc/2GCO6kNAM+2EbgHOCRKozt2t2SJNWO64RLNfbp\nm27iYqA46HgRuLj8+mjVt/b5rFlLq7b2uSRJY5kz4apLS5fewHXX3cP27b0cd9wELrvsjKq0bkyY\ncBrv/v2De1tSisAc4AdHvo3e3gcqPh5UfyZ88NrnAA0N7Sxb1lzRtc8lSRqNnAmX9mPp0hvo6Pgx\n27evBr7F9u2r6ej4MUuX3lDxsV7/+jO4m5uYQ6kFZQ5wNzfx+tefUfGxslJa+7xjwLGeno4qrH0u\nSdLYZQhX3bnuunvYtevvBhzbtevvuO66yrdUnHDCy4CLuJubaKYUwOEipk49uuJj9bWIwBlVbRHp\n7R16+4CdO8dVZTxJksYiN+tR3XnuuaHXzn7uucr/uLe1NdHT005PTwc/5SIAGhqupLX1nIqOM7hF\npFCAnp7SDpqVbhGZMGHXkMcnTtxd0XEkSRrLnAlX3entHXyr5IGPD0dLy0yWLWumuXkJMIvm5iUs\nW3ZOxYNxli0ibW1NNDS0DzhW+mJxdsXHkiRprHImXHVn/Pjn2L37E0D/lpSPM378c1UZr6VlJi0t\nM4kI7rxzfVXGyLJFpO8LRGfnEnbuHMfEibtpba38FwtJksYyQ7jqzlFHnURv738B5gITgZ3ATCZN\n2lnbwoYh6xaRvi8WkiSpOmxHUd2ZNu2lwCXArcCK8r8vYdq0l9WyrGGxRUSSpPpiCFfd+cIX5nL8\n8Z8EVnMKAazm+OP/ks9//sJal3bY+veeR5xZtd5zSZKUDTfrUV06//yP8ttv/j03Udq98hXv/wh3\n3PHVqo7pdvKSJNU/N+uR9uPTn/4sv/3m33M7MA24HfjtN/+eT3/6szWuTJIkqcSZcNWV1atXc+Pc\nuXu3ke/Tt538x269lQsvrE5bijPhkiTVv0rNhBvCVVfeEMGdlGbAB9sInAM8UqWfE0O4JEn1z3YU\naQifv/VWLqY0891fkVJv+OdvvTX7oiRJkgYxhKuuXHjhhbzi/R9hDvuCeF8ryive/5GqtaJIkiS9\nGIZw1Z1nnjmBu/kMcyi1oMwB7uYz/O53U2tcmSRJUokhXHWntMX757ibW2kG7uZW4HNV2eJdkiTp\ncLhtverOvi3eL+Sn7Gs/qdYW75IkSS+WM+GqO27xLkmSRjqXKFRdyue76Oxcx9q136e5+XRaW8+u\n+hbvLlEoSVL9c53wQQzhGkqWwdgQLklS/XOdcEmSJGmUMoRLFfLSl7601iVIkqRRwnYU1TVbRCRJ\nUiXZjiJJkiSNUoZwSZIkKWOGcEmSJCljhnBJkiQpY4ZwSZIkKWOG8BFs5cqVtS5BkiRJVWAIH8FW\nrVpV6xIkSZJUBYZwSZIkKWOGcEmSJCljhnBJkiQpY4ZwSZIkKWOGcEmSJCljhnDVtWOPPbbWJUiS\nJL2AIXwEyue7aG5ezL33Hklz82Ly+a5alzRqbd++vdYlSJIkvcD4WheggfL5LhYuXEtPTwcAhQL0\n9LQD0NIys5alSZIkqUKcCR9hli8v7A3gfXp6OujsXFejiiRJklRphvARprd36F9O7Nw5LuNKJEmS\nVC2G8BFmwoRdQx6fOHF3xpVIkiSpWgzhI0xbWxMNDe0DjjU0XElr69k1qkiSJEmVFimlWtdQERGR\n6uWz5PNddHauY8OGh5kxYzqtrWd7U6YkSdIIEBGklGLY18k6uEbEScDXgFcDCbgxpbQ8Io4FVgOv\nATYBH0gp/bb8niuAjwK7gbaUUmGI69ZNCO8ze/Zs1qxZU+syJEmSVFapEF6LdpTngb9MKb0JeCdw\naUScClwOrEspvR64q/yciJgOXAhMB84BbogI22gkSZI0amUeZlNKW1NKD5YfPwP8BJgKvA+4pXza\nLcB55cfnAqtSSs+nlDYBPwPenmnRkiRJUgXVdEY5Il4LnAb8CJicUtpWfmkbMLn8+ARgc7+3baYU\n2iVJkqRRqWY7ZkbEy4A7gIUppR0R+1prUkopIg7U4D3ka0uXLt37eNasWcyaNasitUqSJGlsWr9+\nPevXr6/4dWuyOkpEvAT4LvC9lNLflI/9JzArpbQ1IqYA/5pSemNEXA6QUrqmfN6dwGdTSj8adM26\nujGzWCxy1qmnctdPfkIul6t1OZIkSWIU35gZpSnvm4GH+wJ42XeAD5cffxj4Vr/jcyPiyIiYBpwC\n3J9VvbVQLBZpb2rijm3baG9qolgs1rokSZIkVVAtlih8N9AF/Jh9bSVXUArWtwEn88IlCq+ktETh\nLkrtK2uHuG5dzIT3BfCO7m5yQBFob2yko1BwRlySJKnGRu064dVSDyF8cADfexyDuCRJ0kgwattR\ntH/tCxawaFAAB8gBi7q7aV+woAZVSZIkqdIM4SNIx4oVXNvYyOAO8CJwbWMjHStW1KAqSZIkVZoh\nfATJ5XJ0FAq09wvitqJIkiTVH3vCR6C+3vBF3d2lGXADuCRJ0ojgjZmD1FMIB9cJlyRJGom8MbPO\n5XI5ps6YYQCXJEmqQ4ZwSZIkKWOGcEmSJCljhnBJkiQpY4ZwSZIkKWOGcEmSJCljhnBJkiQpY4Zw\nSZIkKWOGcEmSJCljhnBJkiQpY4ZwSZIkKWOGcEmSJCljhnBJkiQpY4ZwSZIkKWOGcEmSJCljhnBJ\nkiQpY4ZwSZIkKWOGcEmSJCljhnBJkiQpY4ZwSZIkKWOG8BFs3rx5tS5BkiRJVRAppVrXUBERkerl\ns0iSJGlkighSSjHc6zgTLkmSJGXMEC5JkiRlzBAuSZIkZcwQLkmSJGXMEC5JkiRlzBAuSZIkZcwQ\nLkmSJGXMEC5JkiRlzBAuSZIkZcwQLkmSJGXMEC5JkiRlzBAuSZIkZcwQLkmSJGXMEC5JkiRlzBAu\nSZIkZcwQLkmSJGXMEC5JkiRlzBAuSZIkZcwQLkmSJGXMEC5JkiRlzBAuSZIkZcwQLkmSJGXMEC5J\nkiRlzBAuSZIkZcwQLkmSJGXMEC5JkiRlzBAuSZIkZcwQLkmSJGXMEC5JkiRlzBAuSZIkZcwQLknS\n/9/e/YXKcdZhHP8+JEZqbKSRSkCrlRKaVlpBaqVUEXshAdEKRbS2RFFLb6pFUhBEpBd66YVaFBFB\nKIpEiKUXin+QiEiqRpq2YAsGW/FPxNhWMYoltj8vzkSWeJIzu3N2ZmfO9wPDzuzMe3jn7LMvP+bM\nnFeSemYRLkmSJPXMIlySJEnqmUW4JEmS1DOLcEmSJKlnFuGSJElSzyzCJUmSpJ5ZhEuSJEk9swiX\nJEmSejaaIjzJ/iRPJPlNkk8M3R+Nw5EjR4buglaQudB6zIXWYy60LKMowpNsA+4D9gNXA7cmuWrY\nXmkMHDy1HnOh9ZgLrcdcaFlGUYQD1wMnquqpqjoDfAu4eeA+SZIkSQsZSxH+SuD3M9t/aN6TJEmS\nRidVNXQfNpTkFmB/Vd3RbN8OvKmqPjpzzOqfiCRJkkavqtL1Z2zfjI704I/AZTPbl7F2Nfx/NuOX\nIUmSJPVhLLejHAP2Jrk8yQ7gvcCDA/dJkiRJWsgoroRX1X+S3AV8H9gGfK2qHh+4W5IkSdJCRnFP\nuCRJkjQlK387ykaT9CTZl+Rokn8nOThPW41Xx1w8leTRJA8n+UV/vdaytcjFbUkeaT7/nyW5tm1b\njVfHXDheTFSLXNzc5OLhJL9KclPbthqvjrmYb7yoqpVdWLv15ARwOfAi4Dhw1TnHXApcB3wGODhP\nW5dxLl1y0ex7Etg99Hm4DJKLG4CXNev7gYfatnUZ59IlF82248UEl5a52Dmzfg1r85U4Xkx46ZKL\nZnuu8WLVr4RvOElPVZ2qqmPAmXnbarS65OIs/5vO9LTJxdGq+nuz+XPgVW3barS65OIsx4vpaZOL\nf85svhT4a9u2Gq0uuTir9Xix6kV4l0l6nOBnurp+tgX8KMmxJHdsas80pHlz8WHguwu21Xh0yQU4\nXkxVq1wkeXeSx4HvAR+bp61GqUsuYM7xYtX/O0qXp0Z94nS6un62N1bVySSXAj9M8kRV/XQzOqZB\ntc5FkrcBHwJunLetRqdLLsDxYqpa5aKqHgAeSPIW4P4k+5bbLQ1soVwAVza75hovVv1K+IaT9Cyp\nrVZbp8+2qk42r6eA77D25yeNX6tcNA/dfRV4V1U9O09bjVKXXDheTNdc3/mmkNoO7G6Oc7yYpoVy\nkeTlzfZc48WqF+HzTNJz7j04TvAzXQvnIslLklzcrO8E3g48tszOqjcb5iLJq4HDwO1VdWKethqt\nhXPheDFpbXJxRZI0628AqKqn27TVaC2ci0XGi5W+HaXOM0lPkjub/V9Jsgf4JbALeCHJ3cDVVXV6\nvbbDnIk2U5dcAK8ADjffn+3AN6rqB0OchzZXm1wAnwYuAb7cZOBMVV1/vraDnIg2VZdcAHtwvJik\nlrm4BTiQ5AxwGnjfhdoOcR7aXF1ywQLjhZP1SJIkST1b9dtRJEmSpMmxCJckSZJ6ZhEuSZIk9cwi\nXJIkSeqZRbgkSZLUM4twSZIkqWcW4ZKk80rymiS3Dt0PSZoai3BJ2uKSXGjittcC7++rL5K0VThZ\njyRNSJIDwEGggEeBQ8CngB3A08BtVfWXJPcCV7BWZP8O+CRwP7Cz+VF3VdXRJA8B+4Anga9X1ed7\nPNBc0ZEAAAFHSURBVB1JmiyLcEmaiCSvAw4DN1TVM0kuAaqq/tbs/wiwr6ruaYrwdwBvrqrnklwE\nvNCs7wW+WVVvTPJW4J6qeucwZyVJ03ShP0FKksblJuBQVT0DUFXPJrkmySFgD2tXw3/bHFvAg1X1\nXLO9A7gvyeuB54G9zfvprfeStIV4T7gkTUfx/0XzF4EvVNW1wJ3ARTP7/jWz/nHgZHPcdcCLl9lR\nSdrqLMIlaTp+DLwnyW6A5nUX8Kdm/wdnjj23WN8F/LlZPwBsa9b/AVy8jM5K0lZmES5JE1FVvwY+\nC/wkyXHgc8C9wLeTHANOsXa1nOZ19qGgLwEfaNpdCZxu3n8EeD7J8SR3L/8sJGlr8MFMSZIkqWde\nCZckSZJ6ZhEuSZIk9cwiXJIkSeqZRbgkSZLUM4twSZIkqWcW4ZIkSVLPLMIlSZKknv0X4POlke5X\n1uEAAAAASUVORK5CYII=\n",
"text": [
""
]
}
],
"prompt_number": 79
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig, ax = plt.subplots(figsize=(12, 8))\n",
"graphics.plot_regress_exog(results, \"carat\", fig);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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8kO6c6wO87/+OmfUDrgb6+fs8a4fuKvcc8Gvn3LHAsWZWus9Ga+rUqVxwwQXs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RTKnnyTH6VUTaA94IKxoegxIFxrfcmqkQkhrCY0dDPBwetITrbHwcGEt3eXXPcwsKZ169bh6elJ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\n87PhHAAAAABJRU5ErkJggg==\n",
"text": [
""
]
}
],
"prompt_number": 80
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# generated data set\n",
"from random import uniform, normalvariate, seed\n",
"from math import sin"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 81
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"seed(123)\n",
"x = [uniform(-3, 3) for _ in xrange(100)]\n",
"y = [_ + sin(_) + normalvariate(mu=100, sigma=.2) for _ in x]\n",
"df = pd.DataFrame([_ for _ in zip(x, y)], columns = ['x', 'y'])\n",
"df = df.sort('x')"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 82
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plt.scatter(df.y, df.x);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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1mtmLgQuBryUQX0WjOCvS0sKjbpzhio7PA9vd/SsJxVatUZwXhAM6zGw1wd/7\nE4lE2CBGd3+tu7/Y3V8MfALY7e5/PeeVYp7p/T8EdarHgKvDYyuAewlWTjwC5OK8Z1xxhsfvBrYk\nHd8838/1wMPhsa8Aa1Ma5zsJfhN6HPjzhOK6j2CyeQr4EcHqnJUEk7nfJygfPb/q/NsIJk2PEK48\nSmmc/wKcBH4B/BC4OG1xEvwwf4aghFj56k5hnDcQzBONEvwgvyZtMdZ87gPAe+a7vjYoiYhkjB6N\nJyKSMUrsIiIZo8QuIpIxSuwiIhmjxC4ikjFK7CIiGaPELiKSMUrsIiIZ8/8BA8h1yphgD88AAAAA\nSUVORK5CYII=\n",
"text": [
""
]
}
],
"prompt_number": 83
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"results = sm.ols(\"y ~ x\", data=df).fit()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 84
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# why does this show up twice??\n",
"# todo: look at the source and figure \n",
"fig, ax = plt.subplots(figsize=(12, 8))\n",
"graphics.plot_regress_exog(results, \"x\", fig);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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eezjuuOMqHdcYr0tERPbwPqdrnRlo1hmiEJ/Px5jx4/crkKmPNkREwsWyTHZN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7Vu3Zpnn322yJ/BgwcPZsCAAXh5edGkSRMqVKjAkiVLAKhQoQJTpkzh6aefpnr16uzbt69IbQlh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\nvsJebdfTxJTfS+VaeH7KdQZ2eCZS+AtwpbU2aprdw5ExpgXwOjDfWvtmq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"text": [
""
]
}
],
"prompt_number": 85
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plt.plot(df.x, results.resid, 'o');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
""
]
}
],
"prompt_number": 86
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Heteroskedasticity\n",
"\n",
"* The model isn't right because the variance isn't constant as a function of $x$"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = [uniform(0, 6) for _ in xrange(100)]\n",
"df = pd.DataFrame(x, columns = ['x'])"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 87
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"ygen = lambda x: x + normalvariate(0, .001*x)\n",
"df['y'] = [ygen(x) for x in df.x]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 88
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df = df.sort('x')\n",
"plt.plot(df.x, df.y, 'o');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAWgAAAEACAYAAACeQuziAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nKQW0iIhPKaBFRHxKAS0i4lP/H9gO2pViix0bAAAAAElFTkSuQmCC\n",
"text": [
""
]
}
],
"prompt_number": 89
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"r_hetero = sm.ols(\"y~x\", data=df).fit()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 90
},
{
"cell_type": "code",
"collapsed": false,
"input": [
" plt.plot(df.x, r_hetero.resid, 'o');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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ZfTTtOiXBzBaa2VNm9jdp1yVuZnbIzPYFr29OF3bemdkSM/uSmR0IPqNXRJbL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\ngg==\n",
"text": [
""
]
}
],
"prompt_number": 91
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig, ax = plt.subplots(figsize=(12, 8))\n",
"graphics.plot_regress_exog(r_hetero, \"x\", fig);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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gwYOkpKTUuU1KqcDgcrl46+mnefvppzlw4MAxJbMd4iAx73xenXZ/vapqKqVU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\nqbMMiCRJkiR1lgGRJEmSpM76G2BqXsZZOZthAAAAAElFTkSuQmCC\n",
"text": [
""
]
}
],
"prompt_number": 92
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Residuals highlight stuff you will not see in scatter plots"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Estimating Residual Variation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Model $Y_i = \\beta_0 + \\beta_1 X_i + \\epsilon_i$ where $\\epsilon_i \\sim N(0, \\sigma^2)$."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* The ML estimate of $\\sigma^2$ is $\\frac{1}{n}\\sum_{i=1}^n e_i^2$, the average squared residual."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Most people use $$ \\hat \\sigma^2 = \\frac{1}{n-2}\\sum_{i=1}^n e_i^2. $$\n",
"\n",
"* The $n-2$ instead of $n$ is so that $E[\\hat \\sigma^2] = \\sigma^2$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Diamond Example"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"diamond.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"
\n",
" \n",
" \n",
" \n",
" carat \n",
" price \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" 0.17 \n",
" 355 \n",
" \n",
" \n",
" 1 \n",
" 0.16 \n",
" 328 \n",
" \n",
" \n",
" 2 \n",
" 0.17 \n",
" 350 \n",
" \n",
" \n",
" 3 \n",
" 0.18 \n",
" 325 \n",
" \n",
" \n",
" 4 \n",
" 0.25 \n",
" 642 \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 93,
"text": [
" carat price\n",
"0 0.17 355\n",
"1 0.16 328\n",
"2 0.17 350\n",
"3 0.18 325\n",
"4 0.25 642"
]
}
],
"prompt_number": 93
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"y <- diamond$price; x <- diamond$carat; n <- length(y)\n",
"fit <- lm(y ~ x)\n",
"summary(fit)$sigma\n",
"sqrt(sum(resid(fit)^2) / (n - 2))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"[1] 31.84052\n"
]
}
],
"prompt_number": 94
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"y = 'price'; x = 'carat'\n",
"fit = sm.ols('%s ~ %s' % (y, x, ), data=diamond).fit()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 95
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"e = (fit.predict(diamond) - diamond.price)**2"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 96
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* calculating:\n",
"\n",
"$$ \\hat \\sigma^2 = \\frac{1}{n-2}\\sum_{i=1}^n e_i^2. $$"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from math import sqrt\n",
"sigma = sqrt((e.shape[0]-2)**-1 * e.sum())\n",
"sigma"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 97,
"text": [
"31.840522265031762"
]
}
],
"prompt_number": 97
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Normalized by N-1 by default. This can be changed using the ddof argument\n",
"sqrt(fit.resid.var(ddof=2))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 98,
"text": [
"31.840522265031762"
]
}
],
"prompt_number": 98
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Summarizing Variation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$$ \\sum_{i=1}^n (Y_i - \\bar Y)^2 = \\sum_{i=1}^n (Y_i - \\hat Y_i)^2 + \\sum_{i=1}^n (\\hat Y_i - \\bar Y)^2 $$\n",
"\n",
"Or\n",
"\n",
"Total Variation = Residual Variation + Regression Variation\n",
"\n",
"Define the percent of total varation described by the model as $$ R^2 = \\frac{\\sum_{i=1}^n (\\hat Y_i - \\bar Y)^2}{\\sum_{i=1}^n (Y_i - \\bar Y)^2} = 1 - \\frac{\\sum_{i=1}^n (Y_i - \\hat Y_i)^2}{\\sum_{i=1}^n (Y_i - \\bar Y)^2} $$\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Key: \n",
"\n",
"$Y_i$ - $i^{th}$ obseration of $Y$\n",
"\n",
"$\\hat Y_i$ - Predicted value of $i^{th} Y$\n",
"\n",
"$n$ - number of observations\n",
"\n",
"$\\bar Y$ - Empirical mean of $Y$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Total Variation = $\\sum_{i=1}^n (\\bar Y - Y_i)^2$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Residual Variation = $\\sum_{i=1}^n(\\hat Y_i - Y_i)^2$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Regression Variation = $\\sum_{i=1}^n (\\hat Y_i - \\bar Y)^2$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$R^2 = \\dfrac{\\text{Regression Variation}}{\\text{Total Variation}} = 1 - \\dfrac{\\text{Residual Variation}}{\\text{Total Variation}}$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Relation between $R^2$ and $r$ (the corrrelation)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Recall that $(\\hat Y_i - \\bar Y) = \\hat \\beta_1 (X_i - \\bar X)$ so that \n",
"\n",
"$$ R^2 = \\frac{\\sum_{i=1}^n (\\hat Y_i - \\bar Y)^2}{\\sum_{i=1}^n (Y_i - \\bar Y)^2} = \\hat \\beta_1^2 \\frac{\\sum_{i=1}^n(X_i - \\bar X)^2}{\\sum_{i=1}^n (Y_i - \\bar Y)^2} = Cor(Y, X)^2 $$ Since, recall, $$ \\hat \\beta_1 = Cor(Y, X)\\frac{Sd(Y)}{Sd(X)} $$ So, $R^2$ is literally $r$ squared."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## The pit and pratfalls of solely relying on $R^2$\n",
"Taken from [here](http://matplotlib.org/examples/pylab_examples/anscombe.html)"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from __future__ import print_function\n",
"\"\"\"\n",
"Edward Tufte uses this example from Anscombe to show 4 datasets of x\n",
"and y that have the same mean, standard deviation, and regression\n",
"line, but which are qualitatively different.\n",
"\n",
"matplotlib fun for a rainy day\n",
"\"\"\"\n",
"\n",
"from pylab import *\n",
"\n",
"x = array([10, 8, 13, 9, 11, 14, 6, 4, 12, 7, 5])\n",
"y1 = array([8.04, 6.95, 7.58, 8.81, 8.33, 9.96, 7.24, 4.26, 10.84, 4.82, 5.68])\n",
"y2 = array([9.14, 8.14, 8.74, 8.77, 9.26, 8.10, 6.13, 3.10, 9.13, 7.26, 4.74])\n",
"y3 = array([7.46, 6.77, 12.74, 7.11, 7.81, 8.84, 6.08, 5.39, 8.15, 6.42, 5.73])\n",
"x4 = array([8,8,8,8,8,8,8,19,8,8,8])\n",
"y4 = array([6.58,5.76,7.71,8.84,8.47,7.04,5.25,12.50,5.56,7.91,6.89])\n",
"\n",
"def fit(x):\n",
" return 3+0.5*x\n",
"\n",
"\n",
"\n",
"xfit = array( [amin(x), amax(x) ] )\n",
"\n",
"subplot(221)\n",
"plot(x,y1,'ks', xfit, fit(xfit), 'r-', lw=2)\n",
"axis([2,20,2,14])\n",
"setp(gca(), xticklabels=[], yticks=(4,8,12), xticks=(0,10,20))\n",
"text(3,12, 'I', fontsize=20)\n",
"\n",
"subplot(222)\n",
"plot(x,y2,'ks', xfit, fit(xfit), 'r-', lw=2)\n",
"axis([2,20,2,14])\n",
"setp(gca(), xticklabels=[], yticks=(4,8,12), yticklabels=[], xticks=(0,10,20))\n",
"text(3,12, 'II', fontsize=20)\n",
"\n",
"subplot(223)\n",
"plot(x,y3,'ks', xfit, fit(xfit), 'r-', lw=2)\n",
"axis([2,20,2,14])\n",
"text(3,12, 'III', fontsize=20)\n",
"setp(gca(), yticks=(4,8,12), xticks=(0,10,20))\n",
"\n",
"subplot(224)\n",
"\n",
"xfit = array([amin(x4),amax(x4)])\n",
"plot(x4,y4,'ks', xfit, fit(xfit), 'r-', lw=2)\n",
"axis([2,20,2,14])\n",
"setp(gca(), yticklabels=[], yticks=(4,8,12), xticks=(0,10,20))\n",
"text(3,12, 'IV', fontsize=20)\n",
"\n",
"#verify the stats\n",
"pairs = (x,y1), (x,y2), (x,y3), (x4,y4)\n",
"for x,y in pairs:\n",
" print ('mean=%1.2f, std=%1.2f, r=%1.2f'%(mean(y), std(y), corrcoef(x,y)[0][1]))\n",
"\n",
"show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"mean=7.50, std=1.94, r=0.82\n",
"mean=7.50, std=1.94, r=0.82\n",
"mean=7.50, std=1.94, r=0.82\n",
"mean=7.50, std=1.94, r=0.82\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
""
]
}
],
"prompt_number": 99
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### So that's the bad $R^2$, what about the residual plots"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = array([10, 8, 13, 9, 11, 14, 6, 4, 12, 7, 5])\n",
"y1 = array([8.04, 6.95, 7.58, 8.81, 8.33, 9.96, 7.24, 4.26, 10.84, 4.82, 5.68])\n",
"y2 = array([9.14, 8.14, 8.74, 8.77, 9.26, 8.10, 6.13, 3.10, 9.13, 7.26, 4.74])\n",
"y3 = array([7.46, 6.77, 12.74, 7.11, 7.81, 8.84, 6.08, 5.39, 8.15, 6.42, 5.73])\n",
"x4 = array([8,8,8,8,8,8,8,19,8,8,8])\n",
"y4 = array([6.58,5.76,7.71,8.84,8.47,7.04,5.25,12.50,5.56,7.91,6.89])\n",
"\n",
"df = pd.DataFrame([x, x4, y1, y2, y3, y4]).T\n",
"df.columns = ['x', 'x4', 'y1', 'y2', 'y3', 'y4']\n",
"\n",
"def regress(x, y, data):\n",
" formula = '%s ~ %s' % (y, x, )\n",
" return sm.ols(formula, data=data).fit()\n",
"\n",
"subplot(221)\n",
"plt.plot(df.x, regress('x', 'y1', df).resid, 'ro');\n",
"plt.title('I');\n",
"subplot(222)\n",
"plt.plot(df.x, regress('x', 'y2', df).resid, 'ro');\n",
"plt.title('II');\n",
"subplot(223)\n",
"plt.plot(df.x, regress('x', 'y3', df).resid, 'ro');\n",
"plt.title('III');\n",
"subplot(224)\n",
"plt.plot(df.x, regress('x4', 'y4', df).resid, 'ro');\n",
"plt.title('IV');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
""
]
}
],
"prompt_number": 100
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"** and the residuals are fucked up too **"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" \n",
"\n",
"## Inference in Regression"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Consider the model $$ Y_i = \\beta_0 + \\beta_1 X_i + \\epsilon_i $$\n",
"\n",
"$\\epsilon \\sim N(0, \\sigma^2)$.\n",
"\n",
"We assume that the true model is known.\n",
"\n",
"$\\hat \\beta_0 = \\bar Y - \\hat \\beta_1 \\bar X $\n",
"\n",
"$\\hat \\beta_1 = Cor(X, Y) \\cdot \\dfrac{Sd(Y)}{Sd(X)} $\n",
"\n",
"---\n",
"\n",
"Not sure if this last equation should be $\\beta_1$ or $\\hat \\beta_1$\n",
"\n",
"$\\hat \\beta_1= \\dfrac{\\sum(X_i - \\bar X)(Y_i - \\bar Y)}{\\sum(X_i - \\bar X)^2}$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" \n",
"## Tests for Regression Coefficients"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Review\n",
"* Statistics like $\\frac{\\hat \\theta - \\theta}{\\hat \\sigma_{\\hat \\theta}}$ often have the following properties.\n",
" 1. Is normally distributed and has a finite sample Student's T distribution if the estimated variance is replaced with a sample estimate (under normality assumptions).\n",
" 3. Can be used to test $H_0 : \\theta = \\theta_0$ versus $H_a : \\theta >, <, \\neq \\theta_0$.\n",
" 4. Can be used to create a confidence interval for $\\theta$ via $\\hat \\theta \\pm Q_{1-\\alpha/2} \\hat \\sigma_{\\hat \\theta}$\n",
" where $Q_{1-\\alpha/2}$ is the relevant quantile from either a normal or T distribution.\n",
"* In the case of regression with iid sampling assumptions and normal errors, our inferences will follow\n",
"very similarily to what you saw in your inference class.\n",
"* We won't cover asymptotics for regression analysis, but suffice it to say that under assumptions \n",
"on the ways in which the $X$ values are collected, the iid sampling model, and mean model, \n",
"the normal results hold to create intervals and confidence intervals\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Standard errors (conditioned on X)\n",
"$$\n",
"\\begin{align}\n",
"Var(\\hat \\beta_1) & =\n",
"Var\\left(\\frac{\\sum_{i=1}^n (Y_i - \\bar Y) (X_i - \\bar X)}{\\sum_{i=1}^n (X_i - \\bar X)^2}\\right) \\\\\n",
"& = \\frac{Var\\left(\\sum_{i=1}^n Y_i (X_i - \\bar X) \\right) }{\\left(\\sum_{i=1}^n (X_i - \\bar X)^2 \\right)^2} \\\\\n",
"& = \\frac{\\sum_{i=1}^n \\sigma^2(X_i - \\bar X)^2}{\\left(\\sum_{i=1}^n (X_i - \\bar X)^2 \\right)^2} \\\\\n",
"& = \\frac{\\sigma^2}{\\sum_{i=1}^n (X_i - \\bar X)^2} \\\\\n",
"\\end{align}\n",
"$$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Results\n",
"* $\\sigma_{\\hat \\beta_1}^2 = Var(\\hat \\beta_1) = \\sigma^2 / \\sum_{i=1}^n (X_i - \\bar X)^2$\n",
"* $\\sigma_{\\hat \\beta_0}^2 = Var(\\hat \\beta_0) = \\left(\\frac{1}{n} + \\frac{\\bar X^2}{\\sum_{i=1}^n (X_i - \\bar X)^2 }\\right)\\sigma^2$\n",
"* In practice, $\\sigma$ is replaced by its estimate.\n",
"* It's probably not surprising that under iid Gaussian errors\n",
"$$\n",
"\\frac{\\hat \\beta_j - \\beta_j}{\\hat \\sigma_{\\hat \\beta_j}}\n",
"$$\n",
"follows a $t$ distribution with $n-2$ degrees of freedom and a normal distribution for large $n$.\n",
"* This can be used to create confidence intervals and perform\n",
"hypothesis tests."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Example\n",
"$H_0: \\beta_n = 0$\n",
"\n",
"$H_a: \\beta_n \\neq 0$"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R -o diamond\n",
"library(UsingR); data(diamond)\n",
"y <- diamond$price; x <- diamond$carat; n <- length(y)\n",
"beta1 <- cor(y, x) * sd(y) / sd(x)\n",
"beta0 <- mean(y) - beta1 * mean(x)\n",
"e <- y - beta0 - beta1 * x\n",
"sigma <- sqrt(sum(e^2) / (n-2)) \n",
"ssx <- sum((x - mean(x))^2)\n",
"seBeta0 <- (1 / n + mean(x) ^ 2 / ssx) ^ .5 * sigma \n",
"seBeta1 <- sigma / sqrt(ssx)\n",
"tBeta0 <- beta0 / seBeta0; \n",
"tBeta1 <- beta1 / seBeta1\n",
"pBeta0 <- 2 * pt(abs(tBeta0), df = n - 2, lower.tail = FALSE)\n",
"pBeta1 <- 2 * pt(abs(tBeta1), df = n - 2, lower.tail = FALSE)\n",
"coefTable <- rbind(c(beta0, seBeta0, tBeta0, pBeta0), c(beta1, seBeta1, tBeta1, pBeta1))\n",
"colnames(coefTable) <- c(\"Estimate\", \"Std. Error\", \"t value\", \"P(>|t|)\")\n",
"rownames(coefTable) <- c(\"(Intercept)\", \"x\")\n",
"coefTable"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
" Estimate Std. Error t value P(>|t|)\n",
"(Intercept) -259.6259 17.31886 -14.99094 2.523271e-19\n",
"x 3721.0249 81.78588 45.49715 6.751260e-40\n"
]
}
],
"prompt_number": 101
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import scipy.stats as st\n",
"n = 46\n",
"st.t.pdf(abs(1), df = n - 2)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 102,
"text": [
"0.23924692073493825"
]
}
],
"prompt_number": 102
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = diamond['carat']\n",
"y = diamond['price']\n",
"n = float(len(y))\n",
"beta1 = y.corr(x) * y.std() / x.std() # regression slope\n",
"beta0 = y.mean() - beta1 * x.mean() # regression intercept\n",
"e = y - (beta1 * x + beta0) # errors\n",
"sigma = ((e**2).sum()/(n - 2))**0.5 # unbiased residual mean \n",
"ssx = ((x - x.mean())**2).sum() # sum of squared Xs\n",
"seBeta0 = (1/n + x.mean()**2 / ssx)**0.5 * sigma\n",
"seBeta1 = sigma / ssx**0.5\n",
"tBeta0 = beta0 / seBeta0\n",
"tBeta1 = beta1 / seBeta1\n",
"# TODO: review hypothesis testing\n",
"pBeta0 = 2 * (1-st.t.cdf(abs(tBeta0), df = n - 2))\n",
"pBeta1 = 2 * (1-st.t.cdf(abs(tBeta1), df = n - 2))\n",
"l = [[beta0, seBeta0, tBeta0, pBeta0], \n",
" [beta1, seBeta1, tBeta1, pBeta1]]\n",
"coefTable = pd.DataFrame((_ for _ in l), \n",
" columns = [\"Estimate\", \"Std. Error\", \"t value\", \"P(>|t|)\"],\n",
" index = [\"(Intercept)\", \"x\"])\n",
"\n",
"coefTable"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"
\n",
" \n",
" \n",
" \n",
" Estimate \n",
" Std. Error \n",
" t value \n",
" P(>|t|) \n",
" \n",
" \n",
" \n",
" \n",
" (Intercept) \n",
" -259.625907 \n",
" 17.318856 \n",
" -14.990938 \n",
" 0 \n",
" \n",
" \n",
" x \n",
" 3721.024852 \n",
" 81.785880 \n",
" 45.497155 \n",
" 0 \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 103,
"text": [
" Estimate Std. Error t value P(>|t|)\n",
"(Intercept) -259.625907 17.318856 -14.990938 0\n",
"x 3721.024852 81.785880 45.497155 0"
]
}
],
"prompt_number": 103
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fit = sm.ols(\"price ~ carat\", data=diamond).fit()\n",
"fit.summary()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"OLS Regression Results \n",
"\n",
" Dep. Variable: price R-squared: 0.978 \n",
" \n",
"\n",
" Model: OLS Adj. R-squared: 0.978 \n",
" \n",
"\n",
" Method: Least Squares F-statistic: 2070. \n",
" \n",
"\n",
" Date: Tue, 30 Sep 2014 Prob (F-statistic): 6.75e-40 \n",
" \n",
"\n",
" Time: 15:48:23 Log-Likelihood: -233.20 \n",
" \n",
"\n",
" No. Observations: 48 AIC: 470.4 \n",
" \n",
"\n",
" Df Residuals: 46 BIC: 474.1 \n",
" \n",
"\n",
" Df Model: 1 \n",
" \n",
"
\n",
"\n",
"\n",
" coef std err t P>|t| [95.0% Conf. Int.] \n",
" \n",
"\n",
" Intercept -259.6259 17.319 -14.991 0.000 -294.487 -224.765 \n",
" \n",
"\n",
" carat 3721.0249 81.786 45.497 0.000 3556.398 3885.651 \n",
" \n",
"
\n",
"\n",
"\n",
" Omnibus: 0.739 Durbin-Watson: 1.994 \n",
" \n",
"\n",
" Prob(Omnibus): 0.691 Jarque-Bera (JB): 0.181 \n",
" \n",
"\n",
" Skew: 0.056 Prob(JB): 0.913 \n",
" \n",
"\n",
" Kurtosis: 3.280 Cond. No. 18.5 \n",
" \n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 104,
"text": [
"\n",
"\"\"\"\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: price R-squared: 0.978\n",
"Model: OLS Adj. R-squared: 0.978\n",
"Method: Least Squares F-statistic: 2070.\n",
"Date: Tue, 30 Sep 2014 Prob (F-statistic): 6.75e-40\n",
"Time: 15:48:23 Log-Likelihood: -233.20\n",
"No. Observations: 48 AIC: 470.4\n",
"Df Residuals: 46 BIC: 474.1\n",
"Df Model: 1 \n",
"==============================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"------------------------------------------------------------------------------\n",
"Intercept -259.6259 17.319 -14.991 0.000 -294.487 -224.765\n",
"carat 3721.0249 81.786 45.497 0.000 3556.398 3885.651\n",
"==============================================================================\n",
"Omnibus: 0.739 Durbin-Watson: 1.994\n",
"Prob(Omnibus): 0.691 Jarque-Bera (JB): 0.181\n",
"Skew: 0.056 Prob(JB): 0.913\n",
"Kurtosis: 3.280 Cond. No. 18.5\n",
"==============================================================================\n",
"\"\"\""
]
}
],
"prompt_number": 104
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"data(diamond)\n",
"fit <- lm(\"price ~ carat\", data=diamond)\n",
"summary(fit)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"\n",
"Call:\n",
"lm(formula = \"price ~ carat\", data = diamond)\n",
"\n",
"Residuals:\n",
" Min 1Q Median 3Q Max \n",
"-85.159 -21.448 -0.869 18.972 79.370 \n",
"\n",
"Coefficients:\n",
" Estimate Std. Error t value Pr(>|t|) \n",
"(Intercept) -259.63 17.32 -14.99 <2e-16 ***\n",
"carat 3721.02 81.79 45.50 <2e-16 ***\n",
"---\n",
"Signif. codes: 0 \u2018***\u2019 0.001 \u2018**\u2019 0.01 \u2018*\u2019 0.05 \u2018.\u2019 0.1 \u2018 \u2019 1\n",
"\n",
"Residual standard error: 31.84 on 46 degrees of freedom\n",
"Multiple R-squared: 0.9783,\tAdjusted R-squared: 0.9778 \n",
"F-statistic: 2070 on 1 and 46 DF, p-value: < 2.2e-16\n",
"\n"
]
}
],
"prompt_number": 105
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---\n",
"### Interlude to find Python equivalant of R's:"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"```pt(abs(tBeta1), df = n - 2, lower.tail = FALSE)```"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print ('\\n'.join(st.t.pdf.__doc__.split('\\n')[:100]))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" Probability density function at x of the given RV.\n",
"\n",
" Parameters\n",
" ----------\n",
" x : array_like\n",
" quantiles\n",
" arg1, arg2, arg3,... : array_like\n",
" The shape parameter(s) for the distribution (see docstring of the\n",
" instance object for more information)\n",
" loc : array_like, optional\n",
" location parameter (default=0)\n",
" scale : array_like, optional\n",
" scale parameter (default=1)\n",
"\n",
" Returns\n",
" -------\n",
" pdf : ndarray\n",
" Probability density function evaluated at x\n",
"\n",
" \n"
]
}
],
"prompt_number": 106
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import numpy as np\n",
"x = np.arange(-3, 3, .01)\n",
"ypdf = [st.t.pdf(_, n - 2) for _ in x]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 107
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"ycdf = [1 - st.t.cdf(_, n - 2) for _ in x]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 108
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"f, axarr = plt.subplots(2, sharex=True)\n",
"axarr[0].plot(x, ypdf)\n",
"axarr[0].set_title('PDF')\n",
"axarr[1].plot(x, ycdf)\n",
"axarr[1].set_title('CDF');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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/5O7TUo+/JBZfFtXeU+6+PPWwJTEGurSq8/IiwQOY2WVm9gFwLPDn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\n",
"text": [
""
]
}
],
"prompt_number": 109
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R -o dfR\n",
"# test to figure out wtf the pt function is doing\n",
"require(ggplot2)\n",
"n <- 48\n",
"x <- seq(-3, 3, by=.01)\n",
"y <- pt(x, df = n - 2, lower.tail = FALSE)\n",
"df1 <- data.frame(x, y, 'false')\n",
"names(df1) <- c('x', 'y', 'tail')\n",
"\n",
"y <- pt(x, df = n - 2, lower.tail = TRUE)\n",
"df2 <- data.frame(x, y, 'true')\n",
"names(df2) <- c('x', 'y', 'tail')\n",
"dfR <- rbind(df1, df2)\n",
"ggplot(dfR, aes(x, y, colour=tail)) + geom_line() + theme_bw() + ggtitle(\"Effect of lower.tail parameter in `pt` function\")"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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tTKc1TiEXjK6p6tHowsIAG72GwpRPxoHd3borf8VnjCHX2jVU9M5bxMsSkXfM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\ngg==\n"
}
],
"prompt_number": 110
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So the ```pt``` function creates a cdf"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"dfR = dfR[dfR['tail'] == 'false']"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 111
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"f, axarr = plt.subplots(2, sharex=True)\n",
"axarr[0].plot(dfR['x'], dfR['y'])\n",
"axarr[0].set_title('R CDF')\n",
"axarr[1].plot(x, ycdf)\n",
"axarr[1].set_title('Python CDF');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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RcM6bQG8zq2lm9YAehPqeIlWqdm24+2549VW4/vowVXHjxqijEql8FS6+7O5z\ngXeAmcAk4El3VyKXyPTpE6Ymrl4NXbtqmqLkPi0Ikpz24othiuLtt8Mvf6niz5J9VHxZBFi4MMxs\nqVsXnn027H0uki20ja0IoUboBx+ErXG7dIE33og6IpH0UotcqpUJE0Lr/Jhj4KGHYLfdoo5IpGxq\nkYsk6NkTpk0LBSu6dAmrQ0WynRK5VDsNG4a+8vx8OPFEeOAB2LYt6qhEyk9dK1KtffVV6GqpXTts\nxNW6ddQRiWxPXSsiSey9NxQUhD7zww+H116LOiKRnacWuUjMpElwwQWQlxcGQuvXjzoiEbXIRXZK\njx5hIHTLljAQqqLPki2UyEXiNGgAzzwTNt/q3x8GD4atW6OOSqRs6loRKcXixWEgtGZNeP55DYRK\nNKqsZmfsvG5mtsXMzixPsCKZpm3bUIHouOM0ECqZrcI1O+POew/YCDzt7jv8J68WuWSzjz+G88+H\no4+Ghx/WQKhUnaqq2QlwPTAM+K5ckYpkuO7dw0CoexgI/eSTqCMSKVbhmp1m1oqQ3B+PvaVmt+Sk\nBg3gqafg3nvhpJNg0CANhEpmSEfNzoeA293dzcyAUv8EUM1OyQVnnx2mKl50EYwaFVaEtm0bdVSS\nK6Kq2bmA4uTdlNBPfqW7j0i4lvrIJads3Rr2aXnwQfjjH+GSS8DK7MkU2XkVLixhZrUIg519gSXA\nx5Qw2Bl3/tPAW+7+egmfKZFLTpoxIyTxNm1C0ecWLaKOSHJJhQc7U6nZKVLdHXZYmNXSqVM4hg4N\ng6IiVUULgkTS6JNPQuv8oIPgL3+BPfeMOiLJdtprRaSKdesGU6dCu3ahpT58eNQRSXWgFrlIJfno\nIxgwALp2DYuI9tor6ogkG6lFLhKhI48MA6Ft28Ihh4RpimrLSGVQi1ykCkydCldcAU2bwhNPQPv2\nUUck2UItcpEM0aVLmNly7LGhH/3BB8O+5yLpoBa5SBWbPx+uugrWrYPHHw996CKlUYtcJAPttx+8\n/z4MHAinnALXXAMrV0YdlWQzJXKRCJiF+eazZ4fCFQccAEOGwLZtUUcm2UhdKyIZYOpUuPbakOD/\n/OfQpy4C6loRyRpdusD48WFmy4knwpVXwrJlUUcl2UKJXCRD1KgBl18O8+ZB48Zhmf8f/gAbN0Yd\nmWS6lBJ5srqdZnaBmc0ws5lm9pGZHZr+UEWqh8aNw7a4n3wCM2dChw6h+LP6z6U0SfvIU6nbaWY9\ngdnuvsY26Z6PAAAH2klEQVTM+hH2MD8i4TrqIxcph48+gptvDvPOBw+Gvn2173l1kq4+8qR1O919\ngruvib2cBLQuT8AisqMjj4QJE+BXv4LrroOf/jQkd5EiqSTypHU7E1wOjKxIUCKyPTM45xyYNStM\nW7zggjAoOmVK1JFJJkglkafcH2JmPwUuA3boRxeRiqtVCy69FD7/PCwmOvVUOOOM0J8u1Vey4ssQ\n+sXbxL1uQ2iVbyc2wPkk0M/dV5V0IRVfFkmPOnXCvPNLLw3l5c48Ezp2hDvvhLw89aFns7QXX4bU\n6naaWVvg38CF7j6xlOtosFOkkmzeDC++GAZDd98d7rgjtNhraIJx1qtw8eW4C50IPATUBIa4+6Ci\nmp3u/oSZ/R04A1gc+0qhu3dPuIYSuUgl27oV3ngDBg2CDRvg+utDn3r9+lFHJuWVtkSepmCUyEWq\niDuMGwePPAJjxoRkPnAg7LNP1JHJztISfZFqygyOOgqGDQv7uNSuDT16hMHRt9/WXui5Ri1ykWpi\n40Z46aWwy+LixaGVftllYVtdyVzqWhGREs2aFRL6Cy+EPV0GDAjTGBs2jDoySaRELiJl2rwZRowI\nCX3MmFCK7txz4aSToF69qKMTUCIXkZ2wenWY8fLyy6G+6Mknh1b68cdDgwZRR1d9KZGLSLl8+20Y\nKB0xIuyTfuSRYaD0lFOgtXZSqlJK5CJSYWvXwqhRIamPHAlt28Jxx4VumN691QVT2ZTIRSSttmyB\nSZNg9OhQQHraNOjWLST1Y44JlY7q1Ik6ytyiRC4ilWrdurDwaPRo+Pe/Yf78kMx79QpHz56w555R\nR5ndlMhFpEqtXRsGSsePD8fEiSGRd+kCnTtDp07hsVmzqCPNHkrkIhKpbdtgzpzQBTNtGkyfHh53\n2SUk9EMPhQMOCDs3dugQytzJ9tKSyGOl24o2zPq7u99fwjmPACcCG4EB7j6thHOUyEUE97CydPr0\nUJN03jyYOzccDRqEpN6xY1hx2q4dtG8fHnffvXpuz1vhRJ5ivc7+wEB3729mPYCHE+t1xs7L6URe\nUFCQ0/ur5/L95fK9Qfbcnzt8801I6HPmwIIFsGhROBYuDK37du3C0bYttGgRju++K+CEE/Jo0SJ0\n4+Ta1r2pJPJkhSV+rNcZu2BRvc45ceecCjwL4O6TzKyxmTVz9+XljjwLZcv/LOWVy/eXy/cG2XN/\nZmGOeuvWYRZMotWrixP74sWwdCmMHQvjxhXw4ot5LF0aztlzz5DgmzQJxx57FD8mPm/QIBy77Zbd\nvwCSJfKS6nX2SOGc1kC1SuQiUrkaNw6DpZ06bf9+fn44AAoLYfnykORXroQVK8LjypWhVT9lyvbv\nr1sH69eHDcXq1i1O7PXrFz8vSvS77lryUbduye/XqRNK89WuHR6LjvjXiZ+V95dJskSeal9IYrM/\nd/tQRCRj1a5d3KrfGdu2hUIc69YVH+vXFz/fsAH++1/44QfYtCkcq1aF1yUdmzaFXyqFhWHu/ZYt\n2z9PfF30vEaN7ZP8SSelFn+yPvIjgHx37xd7fQewLX7A08z+ChS4+9DY67nA0YldK2am5C4iUg4V\n7SOfDOxvZu0I9TrPAc5LOGcEMBAYGkv8q0vqH08WiIiIlE+Zidzdt5jZQGAUxfU658TX63T3kWbW\n38zmAxuASys9ahER+VGVLQgSEZHKUaUTbszsHjObYWbTzex9M2tTlT+/MpnZH81sTuz+XjezRlHH\nlE5mdraZzTKzrWbWJep40sXM+pnZXDP7wsxuizqedDKzp8xsuZl9GnUslcHM2pjZmNh/l5+Z2Q1R\nx5QuZrarmU2K5crZZjaozPOrskVuZg3cfV3s+fXAYe5+RZUFUInM7DjgfXffZmaDAdz99ojDShsz\n6whsA54Abnb3qRGHVGGpLHjLZmbWB1gPPOfuh0QdT7qZWXOgubtPN7P6wBTg9Bz691fP3TeaWS3g\nQ+AWd/+wpHOrtEVelMRj6gPfV+XPr0zu/p67b4u9nESYS58z3H2uu38edRxp9uOCN3cvBIoWvOUE\ndx8HrIo6jsri7svcfXrs+XrCQsWW0UaVPu6+Mfa0DmGMcmVp51b5WiYzu9fMFgOXAIOr+udXkcuA\nkVEHIUmVtJitVUSxSAXEZtZ1JjSicoKZ1TCz6YTFlWPcfXZp5yabflieH/4e0LyEj+5097fc/dfA\nr83sduBPZNEsl2T3Fjvn18Bmd3+pSoNLg1TuL8dopD8HxLpVhgE3xlrmOSH2F36n2HjbKDPLc/eC\nks5NeyJ39+NSPPUlsqzVmuzezGwA0B/oWyUBpdlO/LvLFd8A8QPubQitcskSZlYbeA14wd2HRx1P\nZXD3NWb2T6ArUFDSOVU9a2X/uJenATtsd5utYtv9/go4zd1/iDqeSpYri7t+XPBmZnUIC95GRByT\npMjMDBgCzHb3h6KOJ53MrKmZNY49rwscRxn5sqpnrQwDOgBbgS+Ba9z92yoLoBKZ2ReEQYmiAYkJ\n7n5thCGllZmdATwCNAXWANPc/cRoo6o4MzuR4v32h7h7mdO8somZvQwcDTQBvgV+5+5PRxtV+phZ\nb2AsMJPibrI73P2d6KJKDzM7hLCrbI3Y8by7/7HU87UgSEQku2XxDrwiIgJK5CIiWU+JXEQkyymR\ni4hkOSVyEZEsp0QuIpLllMhFRLKcErmISJb7f+4puDgSA7uOAAAAAElFTkSuQmCC\n",
"text": [
""
]
}
],
"prompt_number": 112
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### End Interlude\n",
"---"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Getting a confidence interval"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"sumCoef <- summary(fit)$coefficients\n",
"sumCoef"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
" Estimate Std. Error t value Pr(>|t|)\n",
"(Intercept) -259.6259 17.31886 -14.99094 2.523271e-19\n",
"carat 3721.0249 81.78588 45.49715 6.751260e-40\n"
]
}
],
"prompt_number": 113
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"sumCoef <- summary(fit)$coefficients\n",
"sumCoef[1,1] + c(-1, 1) * qt(.975, df = fit$df) * sumCoef[1, 2]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"[1] -294.4870 -224.7649\n"
]
}
],
"prompt_number": 114
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"sumCoef[2,1] + c(-1, 1) * qt(.975, df = fit$df) * sumCoef[2, 2]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"[1] 3556.398 3885.651\n"
]
}
],
"prompt_number": 115
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"coefTable['Estimate']['x'] + pd.Series([-1, 1]) * coefTable['Std. Error']['x'] * st.t.ppf(.975, fit.df_resid)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 116,
"text": [
"0 3556.398413\n",
"1 3885.651290\n",
"dtype: float64"
]
}
],
"prompt_number": 116
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"coefTable['Estimate']['(Intercept)'] + pd.Series([-1, 1]) * coefTable['Std. Error']['(Intercept)'] * st.t.ppf(.975, fit.df_resid)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 117,
"text": [
"0 -294.486957\n",
"1 -224.764858\n",
"dtype: float64"
]
}
],
"prompt_number": 117
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---\n",
"WTF are these different R t-distribution functions doing"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"require(reshape)\n",
"require(ggplot2)\n",
"n <- 3\n",
"by <- 0.001\n",
"x <- seq(-n, n, by)\n",
"qt <- qt(x, df = 30)\n",
"pt <- pt(x, df=30)\n",
"dt <- dt(x, df=30)\n",
"rt <- rt(x, df=30)\n",
"\n",
"df <- data.frame(x, qt, pt, dt, rt)\n",
"names(df) <- c('x', 'qt\\ndensity', 'pt\\ndistribution', 'dt\\nquantile', 'rt\\nrandom')\n",
"mdf <- melt.data.frame(df, id = c('x'))\n",
"g <- ggplot(mdf, aes(x, value, colour=variable)) + geom_point(alpha=0.1)\n",
"g <- g + facet_wrap(~variable, scale='free_y') + theme_bw()\n",
"g <- g + ggtitle(\"R Functions for T-Distribution\") + theme(legend.position=\"none\")\n",
"g <- g + ylab('f(x)')\n",
"g"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"Loading required package: reshape\n",
"Loading required package: plyr\n",
"\n",
"Attaching package: \u2018plyr\u2019\n",
"\n",
"The following object is masked from \u2018package:Hmisc\u2019:\n",
"\n",
" is.discrete, summarize\n",
"\n",
"\n",
"Attaching package: \u2018reshape\u2019\n",
"\n",
"The following object is masked from \u2018package:plyr\u2019:\n",
"\n",
" rename, round_any\n",
"\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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HCCw4rYFaesmSJWpbycWLF6t9nqNiIDcJAhYg8Oq3o2npL/8Oa3QbKXsfdTQ7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r+HBatDHrYye8Mpyw5+zaiKVY404C6//4DWEKpydVmFh0u1zSdOzufHbduJELltfEKZotq/HM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\nAElFTkSuQmCC\n"
}
],
"prompt_number": 118
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* `pt` and `qt` are the opposite of eachother. \n",
"* The input of `pt` is a $z$ score and you get back the $P(z>X)$\n",
"* The input of `qt` is some $p, p\\in [0, 1]$. You get back a $z$ such that $P(z>X) = p$\n",
"\n",
"---"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = np.arange(-3, 3, .001)\n",
"dt = st.t.pdf(x, 30)\n",
"qt = st.t.ppf(x, 30)\n",
"pt = st.t.cdf(x, 30)\n",
"f, axarr = plt.subplots(3, sharex=True)\n",
"axarr[0].plot(x, dt)\n",
"axarr[0].set_title('Python st.t.pdf = R dt')\n",
"axarr[1].plot(x, qt)\n",
"axarr[1].set_title('Python st.t.ppf = R qt')\n",
"axarr[2].plot(x, pt)\n",
"axarr[2].set_title('Python st.t.cdf = R pt');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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TFSNeQ1W3Sp4nVvNgd1U9J8uiVYp8ldtJTjot+KexlMHRDAf2VdUDgGlAmQtk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\n",
"text": [
""
]
}
],
"prompt_number": 119
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"st.t.ppf(.975, 46)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 120,
"text": [
"2.0128955952945886"
]
}
],
"prompt_number": 120
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"st.norm.ppf(.975)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 121,
"text": [
"1.959963984540054"
]
}
],
"prompt_number": 121
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"qt(.975, df = fit$df)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"[1] 2.012896\n"
]
}
],
"prompt_number": 122
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" \n",
"## Prediction of Outcomes"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Consider predicting $Y$ at a value of $X$\n",
" * Predicting the price of a diamond given the carat\n",
" * Predicting the height of a child given the height of the parents\n",
"* The obvious estimate for prediction at point $x_0$ is \n",
"$$\n",
"\\hat \\beta_0 + \\hat \\beta_1 x_0\n",
"$$\n",
"* A standard error is needed to create a prediction interval.\n",
"* There's a distinction between intervals for the regression\n",
" line at point $x_0$ and the prediction of what a $y$ would be\n",
" at point $x_0$. \n",
"* Line at $x_0$ se, $\\hat \\sigma\\sqrt{\\frac{1}{n} + \\frac{(x_0 - \\bar X)^2}{\\sum_{i=1}^n (X_i - \\bar X)^2}}$\n",
"* Prediction interval se at $x_0$, $\\hat \\sigma\\sqrt{1 + \\frac{1}{n} + \\frac{(x_0 - \\bar X)^2}{\\sum_{i=1}^n (X_i - \\bar X)^2}}$\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" \n",
"\n",
"### Confidence Intervals"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$\\theta$ via $\\hat \\theta \\pm Q_{1-\\alpha/2} \\hat \\sigma_{\\hat \\theta}$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Plotting the prediction intervals"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"data(diamond)\n",
"x <- diamond$carat; y <- diamond$price\n",
"plot(x, y, frame=FALSE,xlab=\"Carat\",ylab=\"Dollars\",pch=21,col=\"black\", bg=\"lightblue\", cex=2)\n",
"abline(fit, lwd = 2)\n",
"xVals <- seq(min(x), max(x), by = .01)\n",
"yVals <- beta0 + beta1 * xVals\n",
"se1 <- sigma * sqrt(1 / n + (xVals - mean(x))^2/ssx) # orange\n",
"se2 <- sigma * sqrt(1 + 1 / n + (xVals - mean(x))^2/ssx) # blue\n",
"lines(xVals, yVals + 2 * se1, col='orange')\n",
"lines(xVals, yVals - 2 * se1, col='orange')\n",
"lines(xVals, yVals + 2 * se2, col='blue')\n",
"lines(xVals, yVals - 2 * se2, col='blue')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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NgGKfXuPL083samR20Knek2Xg+UVQrx7QtPMQaGFNRm0/tG7cuIFy5crhwoULmD9/PmrX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\nHdOtAlnlav369She3JpAh3r9CClujEXKqrVwK0EtJL16XT9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3CZBL8ubzSe5ud2Z297ub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\n7kc5lfMZ7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}
],
"prompt_number": 123
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"black line = OLS regression line\n",
"\n",
"orange lines = standard error line\n",
"\n",
"blue lines = standard error prediction interval"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Discussion\n",
"* Both intervals have varying widths.\n",
" * Least width at the mean of the Xs.\n",
"* We are quite confident in the regression line, so that\n",
" interval is very narrow.\n",
" * If we knew $\\beta_0$ and $\\beta_1$ this interval would have zero width.\n",
"* The prediction interval must incorporate the variabilibity\n",
" in the data around the line.\n",
" * Even if we knew $\\beta_0$ and $\\beta_1$ this interval would still have width.\n",
" \n",
"*ok... I'm taking this one on faith*"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" \n",
"## Quiz 2"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### q1\n",
"\n",
"Consider the following data with x as the predictor and y \n",
"as as the outcome.\n",
"\n",
"Give a P-value for the two sided hypothesis test of whether \n",
"\u03b21 from a linear regression model is 0 or not."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = [0.61, 0.93, 0.83, 0.35, 0.54, 0.16, 0.91, 0.62, 0.62]\n",
"y = [0.67, 0.84, 0.6, 0.18, 0.85, 0.47, 1.1, 0.65, 0.36]\n",
"df = pd.DataFrame(zip(x, y), columns = ['x', 'y'])"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 124
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$\\beta_1 = Cor(x, y) \\cdot \\dfrac{Sd_y}{Sd_x}$\n",
"\n",
"$\\sigma_{\\hat \\beta_1}^2 = Var(\\hat \\beta_1) = \\dfrac{\\sigma^2}{\\sum_{i=1}^n (X_i - \\bar X)^2}$\n",
"\n",
"$ \\hat \\sigma^2 = \\frac{1}{n-2}\\sum_{i=1}^n e_i^2 $\n",
"\n",
"$ ssx = {\\sum_{i=1}^n (X_i - \\bar X)^2}$ (convenience value)\n",
"\n",
"$\\hat \\beta_0 = \\bar Y - \\hat \\beta_1 \\bar X $\n",
"\n",
"$ p = \\dfrac{\\mu - \\mu:H_o}{\\sigma}$"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from math import sqrt\n",
"x = df['x']\n",
"y = df['y']\n",
"n = len(x)\n",
"beta1 = y.corr(x) * (y.std() / x.std())\n",
"beta0 = y.mean() - beta1 * x.mean()\n",
"ssx = ((x - mean(x))**2).sum()\n",
"yhat = beta0 + beta1 * x\n",
"e = y - yhat\n",
"sigma = sqrt(1.0/(n-2) * (e**2).sum())\n",
"se_beta1 = sqrt((sigma**2 / ssx))\n",
"p = beta1 / se_beta1\n",
"p"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 125,
"text": [
"2.3254912115169395"
]
}
],
"prompt_number": 125
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"results = sm.ols('y~x', data=df).fit().summary()\n",
"results"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stderr",
"text": [
"/Users/idris/.virtualenvs/regres/lib/python2.7/site-packages/scipy/stats/stats.py:1205: UserWarning: kurtosistest only valid for n>=20 ... continuing anyway, n=9\n",
" int(n))\n"
]
},
{
"html": [
"\n",
"OLS Regression Results \n",
"\n",
" Dep. Variable: y R-squared: 0.436 \n",
" \n",
"\n",
" Model: OLS Adj. R-squared: 0.355 \n",
" \n",
"\n",
" Method: Least Squares F-statistic: 5.408 \n",
" \n",
"\n",
" Date: Tue, 30 Sep 2014 Prob (F-statistic): 0.0530 \n",
" \n",
"\n",
" Time: 15:48:27 Log-Likelihood: 1.8658 \n",
" \n",
"\n",
" No. Observations: 9 AIC: 0.2684 \n",
" \n",
"\n",
" Df Residuals: 7 BIC: 0.6629 \n",
" \n",
"\n",
" Df Model: 1 \n",
" \n",
"
\n",
"\n",
"\n",
" coef std err t P>|t| [95.0% Conf. Int.] \n",
" \n",
"\n",
" Intercept 0.1885 0.206 0.914 0.391 -0.299 0.676 \n",
" \n",
"\n",
" x 0.7224 0.311 2.325 0.053 -0.012 1.457 \n",
" \n",
"
\n",
"\n",
"\n",
" Omnibus: 1.435 Durbin-Watson: 1.384 \n",
" \n",
"\n",
" Prob(Omnibus): 0.488 Jarque-Bera (JB): 0.698 \n",
" \n",
"\n",
" Skew: -0.067 Prob(JB): 0.705 \n",
" \n",
"\n",
" Kurtosis: 1.642 Cond. No. 5.85 \n",
" \n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 126,
"text": [
"\n",
"\"\"\"\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: y R-squared: 0.436\n",
"Model: OLS Adj. R-squared: 0.355\n",
"Method: Least Squares F-statistic: 5.408\n",
"Date: Tue, 30 Sep 2014 Prob (F-statistic): 0.0530\n",
"Time: 15:48:27 Log-Likelihood: 1.8658\n",
"No. Observations: 9 AIC: 0.2684\n",
"Df Residuals: 7 BIC: 0.6629\n",
"Df Model: 1 \n",
"==============================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"------------------------------------------------------------------------------\n",
"Intercept 0.1885 0.206 0.914 0.391 -0.299 0.676\n",
"x 0.7224 0.311 2.325 0.053 -0.012 1.457\n",
"==============================================================================\n",
"Omnibus: 1.435 Durbin-Watson: 1.384\n",
"Prob(Omnibus): 0.488 Jarque-Bera (JB): 0.698\n",
"Skew: -0.067 Prob(JB): 0.705\n",
"Kurtosis: 1.642 Cond. No. 5.85\n",
"==============================================================================\n",
"\"\"\""
]
}
],
"prompt_number": 126
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"####q2 "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Consider the previous problem, give the estimate of the residual standard deviation."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sigma"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 127,
"text": [
"0.2229980659078784"
]
}
],
"prompt_number": 127
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### q3"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In the mtcars data set, fit a linear regression model of weight (predictor) on mpg (outcome). Get a 95% confidence interval for the expected mpg at the average weight. What is the lower endpoint?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R -o mtcars\n",
"data(mtcars)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 128
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"r = sm.ols('mpg ~ I(wt - wt.mean())', data=mtcars).fit()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 129
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"alpha = 0.05\n",
"20.0906 + pd.Series([-1, 1]) * st.t.ppf(1 - alpha/2, 30) * .538"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 130,
"text": [
"0 18.991857\n",
"1 21.189343\n",
"dtype: float64"
]
}
],
"prompt_number": 130
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"t = r.summary().tables[1]\n",
"print (t.as_text())"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"=====================================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"-------------------------------------------------------------------------------------\n",
"Intercept 20.0906 0.538 37.313 0.000 18.991 21.190\n",
"I(wt - wt.mean()) -5.3445 0.559 -9.559 0.000 -6.486 -4.203\n",
"=====================================================================================\n"
]
}
],
"prompt_number": 131
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"(20.0906 - 18.991) / .538"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 132,
"text": [
"2.043866171003715"
]
}
],
"prompt_number": 132
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### q4"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Consider again the ```mtcars``` data set and a linear regression model with mpg as predicted by weight (1,000 lbs). A new car is coming weighing 3000 pounds. Construct a 95% prediction interval for its mpg. What is the upper endpoint?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Prediction interval se at $x_0$, \n",
"\n",
"$\\hat \\sigma\\sqrt{1 + \\frac{1}{n} + \\frac{(x_0 - \\bar X)^2}{\\sum_{i=1}^n (X_i - \\bar X)^2}}$"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"data(diamond)\n",
"x <- diamond$carat; y <- diamond$price\n",
"xVals <- seq(min(x), max(x), by = .01)\n",
"yVals <- beta0 + beta1 * xVals\n",
"se1 <- sigma * sqrt(1 / n + (xVals - mean(x))^2/ssx) # orange\n",
"se2 <- sigma * sqrt(1 + 1 / n + (xVals - mean(x))^2/ssx) # blue"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 133
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = mtcars['wt']\n",
"y = mtcars['mpg']\n",
"\n",
"n = len(x)\n",
"ssx = (1.0/n) * ((x- x.mean())**2).sum()\n",
"e = (r.resid - x)\n",
"sigma = sqrt(1.0/(n-2) * (e**2).sum())\n",
"xVals = 3\n",
"se = sigma * sqrt(1 + 1 / n + (xVals - mean(x))**2/ssx)\n",
"se"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 134,
"text": [
"4.731991939031135"
]
}
],
"prompt_number": 134
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"(3 - mtcars.wt.mean()) * r.params[1] + r.params[0] + pd.Series([-1, 1]) * se * st.norm.ppf(.975)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 135,
"text": [
"0 11.977178\n",
"1 30.526245\n",
"dtype: float64"
]
}
],
"prompt_number": 135
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### q6"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Consider again the mtcars data set and a linear regression model with mpg as predicted by weight (in 1,000 lbs). A \u201cshort\u201d ton is defined as 2,000 lbs. Construct a 95% confidence interval for the expected change in mpg per 1 short ton increase in weight. Give the lower endpoint."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sm.ols('mpg ~ I(wt/2)', data=mtcars).fit().summary()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"OLS Regression Results \n",
"\n",
" Dep. Variable: mpg R-squared: 0.753 \n",
" \n",
"\n",
" Model: OLS Adj. R-squared: 0.745 \n",
" \n",
"\n",
" Method: Least Squares F-statistic: 91.38 \n",
" \n",
"\n",
" Date: Tue, 30 Sep 2014 Prob (F-statistic): 1.29e-10 \n",
" \n",
"\n",
" Time: 15:48:27 Log-Likelihood: -80.015 \n",
" \n",
"\n",
" No. Observations: 32 AIC: 164.0 \n",
" \n",
"\n",
" Df Residuals: 30 BIC: 167.0 \n",
" \n",
"\n",
" Df Model: 1 \n",
" \n",
"
\n",
"\n",
"\n",
" coef std err t P>|t| [95.0% Conf. Int.] \n",
" \n",
"\n",
" Intercept 37.2851 1.878 19.858 0.000 33.450 41.120 \n",
" \n",
"\n",
" I(wt / 2) -10.6889 1.118 -9.559 0.000 -12.973 -8.405 \n",
" \n",
"
\n",
"\n",
"\n",
" Omnibus: 2.988 Durbin-Watson: 1.252 \n",
" \n",
"\n",
" Prob(Omnibus): 0.225 Jarque-Bera (JB): 2.399 \n",
" \n",
"\n",
" Skew: 0.668 Prob(JB): 0.301 \n",
" \n",
"\n",
" Kurtosis: 2.877 Cond. No. 7.80 \n",
" \n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 136,
"text": [
"\n",
"\"\"\"\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: mpg R-squared: 0.753\n",
"Model: OLS Adj. R-squared: 0.745\n",
"Method: Least Squares F-statistic: 91.38\n",
"Date: Tue, 30 Sep 2014 Prob (F-statistic): 1.29e-10\n",
"Time: 15:48:27 Log-Likelihood: -80.015\n",
"No. Observations: 32 AIC: 164.0\n",
"Df Residuals: 30 BIC: 167.0\n",
"Df Model: 1 \n",
"==============================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"------------------------------------------------------------------------------\n",
"Intercept 37.2851 1.878 19.858 0.000 33.450 41.120\n",
"I(wt / 2) -10.6889 1.118 -9.559 0.000 -12.973 -8.405\n",
"==============================================================================\n",
"Omnibus: 2.988 Durbin-Watson: 1.252\n",
"Prob(Omnibus): 0.225 Jarque-Bera (JB): 2.399\n",
"Skew: 0.668 Prob(JB): 0.301\n",
"Kurtosis: 2.877 Cond. No. 7.80\n",
"==============================================================================\n",
"\"\"\""
]
}
],
"prompt_number": 136
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### q7"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"r.resid.sum()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 137,
"text": [
"-2.9132252166164108e-13"
]
}
],
"prompt_number": 137
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" \n",
"---\n",
"# Week 3"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" \n",
"## Multivariate Regressions"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* The general linear model extends simple linear regression (SLR)\n",
"by adding terms linearly into the model.\n",
"$$\n",
"Y_i = \\beta_1 X_{1i} + \\beta_2 X_{2i} + \\ldots +\n",
"\\beta_{p} X_{pi} + \\epsilon_{i}\n",
"= \\sum_{k=1}^p X_{ik} \\beta_j + \\epsilon_{i}\n",
"$$\n",
"* Here $X_{1i}=1$ typically, so that an intercept is included.\n",
"* Least squares (and hence ML estimates under iid Gaussianity\n",
"of the errors) minimizes\n",
"$$\n",
"\\sum_{i=1}^n \\left(Y_i - \\sum_{k=1}^p X_{ki} \\beta_j\\right)^2\n",
"$$\n",
"* Note, the important linearity is linearity in the coefficients.\n",
"Thus\n",
"$$\n",
"Y_i = \\beta_1 X_{1i}^2 + \\beta_2 X_{2i}^2 + \\ldots +\n",
"\\beta_{p} X_{pi}^2 + \\epsilon_{i}\n",
"$$\n",
"is still a linear model. (We've just squared the elements of the\n",
"predictor variables.)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### How to get estimates\n",
"The real way requires linear algebra... ( and gradient descent for data too expensive to inverse)\n",
"\n",
"So skipping a bunch of math,\n",
"\n",
"We get that\n",
"$$\n",
"\\hat \\beta_1 = \\frac{\\sum_{i=1}^n e_{i, Y | X_2} e_{i, X_1 | X_2}}{\\sum_{i=1}^n e_{i, X_1 | X_2}^2}\n",
"$$\n",
"\n",
"* That is, the regression estimate for $\\beta_1$ is the regression\n",
"through the origin estimate having regressed $X_2$ out of both\n",
"the response and the predictor.\n",
"* (Similarly, the regression estimate for $\\beta_2$ is the regression through the origin estimate having regressed $X_1$ out of both the response and the predictor.)\n",
"* More generally, multivariate regression estimates are exactly those having removed the linear relationship of the other variables\n",
"from both the regressor and response."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" \n",
"## Multivariable regression examples"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Swiss fertility data"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"library(datasets); data(swiss); require(stats); require(graphics)\n",
"pairs(swiss, panel = panel.smooth, main = \"Swiss data\", col = 3 + (swiss$Catholic > 50))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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j2HzgHz/2+OnjF9oeaRe6dcsi+To4ALQ1UsK1OlD4eHAg76AqmZ6jVtWd1+63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aSQnpVlLdrLJrLUy9J65Wcamaizp3BvLnh/RVBkaPJkDQFktu9cXY1pvwy/je+DWkJ3buKaku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\nV+MLT4nseY7EwC+m1lB4chHAIgSc0OKiSESghksd0Ra3qHSylfcXq4XXxZB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0vt97ANbn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mBgfhX8wuhbatP0Mz8LnQs5hSZZWymY0l65BqgyfSeDjzzu0kbSvVicvrG0aXS8IrZLecp3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\nQmCC\n"
}
],
"prompt_number": 138
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R -o swiss -w 960 -h 960\n",
"require(GGally)\n",
"library(datasets); \n",
"data(swiss); \n",
"theme_set(theme_bw())\n",
"swiss$cath_majority = factor(swiss$Catholic >= 50)\n",
"ggpairs(swiss, \n",
" lower = list(continuous = \"smooth\"),\n",
" colour = \"cath_majority\"\n",
")"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"Loading required package: GGally\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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DPttuI+kG8hH0UKNOmw6C/BbzD0T63hOJIzwfbCOx+z7oMYYKuJemc1+Xit/Q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Ku0uyz0bmBhtBMLtxB2B/l99NMWzVj49VNmDOG2zRefUcGcH9USSFt5qaTSBARX+PcWFRWpCM/h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TpRKbTwAo+36cMPmq3a+mWMGo0tYJaL0e6W3SzZtlW4jtj5K927R9Kx1VcpsMp76H54zl1s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\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J4sCYbeUP2MYBFDD4knVtZiuP3toUl175Ge2Ell62l44AvaMBzm4FEGtomfdKORAw+QMc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6wSmZ9Ow8AezfBCMHH7yafLD1d9LJMRxTv7M58VF6J7Z3IrJmujWY728+0srZu1Pj39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DwCHQnxCwq8JoTiAMc+WqPdKf0u94LW4EzjzzTM869L/8y7+Y7du3e+rQA9XAWHHnhOPOIdB3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\nIASEgBBIIfD/ALLKnA/8b82yAAAAAElFTkSuQmCC\n"
}
],
"prompt_number": 139
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"_ = pd.scatter_matrix(swiss, figsize=(12,8), diagonal='kde');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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j8os2ZlD7wOrVMHIkfOc7cPHFgVQhcqREJZL63waWqGKyizYmv+hisos2Jr9o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\n7ieuClZpOjth/Hhndvrcc4OuTTypq3N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0P2qAvsDnXFxiOdCkqhtFZKaI7AMsUdUmL+tZ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qAJeFdrfb1S6kZgHDESu+QruRhyRnAOaR+JkTpqQepCcJPSUpg1C84/H959F3r08FaeP/4RHnzQ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\nJfD/AQM2Xwd37RXcAAAAAElFTkSuQmCC\n",
"text": [
""
]
}
],
"prompt_number": 140
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"try:\n",
" del swiss['cath_majority']\n",
"except KeyError:\n",
" pass\n",
"swiss.columns = [_.replace('.', '_') for _ in swiss.columns]\n",
"y = 'Fertility'\n",
"x = \"+\".join(swiss.columns - [y])\n",
"formula = '%s ~ %s' % (y, x)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 141
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"results1 = sm.ols(formula, data=swiss).fit()\n",
"results1.summary()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"OLS Regression Results \n",
"\n",
" Dep. Variable: Fertility R-squared: 0.707 \n",
" \n",
"\n",
" Model: OLS Adj. R-squared: 0.671 \n",
" \n",
"\n",
" Method: Least Squares F-statistic: 19.76 \n",
" \n",
"\n",
" Date: Tue, 30 Sep 2014 Prob (F-statistic): 5.59e-10 \n",
" \n",
"\n",
" Time: 15:48:45 Log-Likelihood: -156.04 \n",
" \n",
"\n",
" No. Observations: 47 AIC: 324.1 \n",
" \n",
"\n",
" Df Residuals: 41 BIC: 335.2 \n",
" \n",
"\n",
" Df Model: 5 \n",
" \n",
"
\n",
"\n",
"\n",
" coef std err t P>|t| [95.0% Conf. Int.] \n",
" \n",
"\n",
" Intercept 66.9152 10.706 6.250 0.000 45.294 88.536 \n",
" \n",
"\n",
" Agriculture -0.1721 0.070 -2.448 0.019 -0.314 -0.030 \n",
" \n",
"\n",
" Catholic 0.1041 0.035 2.953 0.005 0.033 0.175 \n",
" \n",
"\n",
" Education -0.8709 0.183 -4.758 0.000 -1.241 -0.501 \n",
" \n",
"\n",
" Examination -0.2580 0.254 -1.016 0.315 -0.771 0.255 \n",
" \n",
"\n",
" Infant_Mortality 1.0770 0.382 2.822 0.007 0.306 1.848 \n",
" \n",
"
\n",
"\n",
"\n",
" Omnibus: 0.058 Durbin-Watson: 1.454 \n",
" \n",
"\n",
" Prob(Omnibus): 0.971 Jarque-Bera (JB): 0.155 \n",
" \n",
"\n",
" Skew: -0.077 Prob(JB): 0.925 \n",
" \n",
"\n",
" Kurtosis: 2.764 Cond. No. 807. \n",
" \n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 142,
"text": [
"\n",
"\"\"\"\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: Fertility R-squared: 0.707\n",
"Model: OLS Adj. R-squared: 0.671\n",
"Method: Least Squares F-statistic: 19.76\n",
"Date: Tue, 30 Sep 2014 Prob (F-statistic): 5.59e-10\n",
"Time: 15:48:45 Log-Likelihood: -156.04\n",
"No. Observations: 47 AIC: 324.1\n",
"Df Residuals: 41 BIC: 335.2\n",
"Df Model: 5 \n",
"====================================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"------------------------------------------------------------------------------------\n",
"Intercept 66.9152 10.706 6.250 0.000 45.294 88.536\n",
"Agriculture -0.1721 0.070 -2.448 0.019 -0.314 -0.030\n",
"Catholic 0.1041 0.035 2.953 0.005 0.033 0.175\n",
"Education -0.8709 0.183 -4.758 0.000 -1.241 -0.501\n",
"Examination -0.2580 0.254 -1.016 0.315 -0.771 0.255\n",
"Infant_Mortality 1.0770 0.382 2.822 0.007 0.306 1.848\n",
"==============================================================================\n",
"Omnibus: 0.058 Durbin-Watson: 1.454\n",
"Prob(Omnibus): 0.971 Jarque-Bera (JB): 0.155\n",
"Skew: -0.077 Prob(JB): 0.925\n",
"Kurtosis: 2.764 Cond. No. 807.\n",
"==============================================================================\n",
"\"\"\""
]
}
],
"prompt_number": 142
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We estimate an expected 0.17 decrease in standardized fertility for every 1% increase in percentage of males involved in agriculture in holding the remaining variables constant."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = 'Agriculture'\n",
"y = 'Fertility'\n",
"results = sm.ols('%s ~ %s' % (y, x, ), data=swiss).fit()\n",
"results.summary()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"OLS Regression Results \n",
"\n",
" Dep. Variable: Fertility R-squared: 0.125 \n",
" \n",
"\n",
" Model: OLS Adj. R-squared: 0.105 \n",
" \n",
"\n",
" Method: Least Squares F-statistic: 6.409 \n",
" \n",
"\n",
" Date: Tue, 30 Sep 2014 Prob (F-statistic): 0.0149 \n",
" \n",
"\n",
" Time: 15:48:45 Log-Likelihood: -181.73 \n",
" \n",
"\n",
" No. Observations: 47 AIC: 367.5 \n",
" \n",
"\n",
" Df Residuals: 45 BIC: 371.2 \n",
" \n",
"\n",
" Df Model: 1 \n",
" \n",
"
\n",
"\n",
"\n",
" coef std err t P>|t| [95.0% Conf. Int.] \n",
" \n",
"\n",
" Intercept 60.3044 4.251 14.185 0.000 51.742 68.867 \n",
" \n",
"\n",
" Agriculture 0.1942 0.077 2.532 0.015 0.040 0.349 \n",
" \n",
"
\n",
"\n",
"\n",
" Omnibus: 0.295 Durbin-Watson: 0.646 \n",
" \n",
"\n",
" Prob(Omnibus): 0.863 Jarque-Bera (JB): 0.481 \n",
" \n",
"\n",
" Skew: -0.095 Prob(JB): 0.786 \n",
" \n",
"\n",
" Kurtosis: 2.542 Cond. No. 137. \n",
" \n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 143,
"text": [
"\n",
"\"\"\"\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: Fertility R-squared: 0.125\n",
"Model: OLS Adj. R-squared: 0.105\n",
"Method: Least Squares F-statistic: 6.409\n",
"Date: Tue, 30 Sep 2014 Prob (F-statistic): 0.0149\n",
"Time: 15:48:45 Log-Likelihood: -181.73\n",
"No. Observations: 47 AIC: 367.5\n",
"Df Residuals: 45 BIC: 371.2\n",
"Df Model: 1 \n",
"===============================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"-------------------------------------------------------------------------------\n",
"Intercept 60.3044 4.251 14.185 0.000 51.742 68.867\n",
"Agriculture 0.1942 0.077 2.532 0.015 0.040 0.349\n",
"==============================================================================\n",
"Omnibus: 0.295 Durbin-Watson: 0.646\n",
"Prob(Omnibus): 0.863 Jarque-Bera (JB): 0.481\n",
"Skew: -0.095 Prob(JB): 0.786\n",
"Kurtosis: 2.542 Cond. No. 137.\n",
"==============================================================================\n",
"\"\"\""
]
}
],
"prompt_number": 143
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Simulation\n",
"How can adjustment reverse the sign of an effect? Let's try a simulation."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R -w 300 -h 300 -o df_simul\n",
"require(ggplot2)\n",
"require(GGally)\n",
"n <- 100; \n",
"x2 <- 1 : n; \n",
"x1 <- .01 * x2 + runif(n, -.1, .1); \n",
"y = -x1 + x2 + rnorm(n, sd = .01)\n",
"df_simul <- data.frame(x1, x2, y)\n",
"theme_set(theme_bw())\n",
"(ggpairs(df_simul))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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F5WeWh9+AgBGVRvD+++8njz32mJkVQsixcUWRISHgExpXhhW+SmGXokMdccQRRkChSSEo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\ntwWN8o4dI7AQOAgrCJ8qm5jxY3iCzUpmBbnPF41QuxjoBw0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}
],
"prompt_number": 144
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"r1 = sm.ols('y ~ x1', data=df_simul).fit()\n",
"r2 = sm.ols('y ~ x1 + x2', data=df_simul).fit()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 145
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"r1.params, r2.params"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 146,
"text": [
"(Intercept 3.187722\n",
" x1 93.551646\n",
" dtype: float64, Intercept 0.000236\n",
" x1 -0.966914\n",
" x2 0.999680\n",
" dtype: float64)"
]
}
],
"prompt_number": 146
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"graphics.plot_regress_exog(r1, 'x1');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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VGs4qTOdFDjESD20p5WucPIeSwRlMYg/fcTX7ZSbJCaVkZAyjtPQ7+vfvzt69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"text": [
""
]
}
],
"prompt_number": 147
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"graphics.plot_regress_exog(r2, \"x1\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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JJRJBWsejKmZgNjbVqa8qq7G+Tw3pX3NezxehuL52xOaTsnKbtECPAuOzzz5j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"text": [
""
]
}
],
"prompt_number": 148
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x1 = df_simul['x1']\n",
"x2 = df_simul['x2']\n",
"y = df_simul['y']\n",
"\n",
"f, axarr = plt.subplots(2, sharex=True)\n",
"axarr[0].plot(x1, y)\n",
"axarr[0].set_title('x1')\n",
"axarr[1].plot(x2, y)\n",
"axarr[1].set_title('x2');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
""
]
}
],
"prompt_number": 149
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"r1 = sm.ols('x1 ~ x2', data=df_simul).fit()\n",
"r2 = sm.ols('y ~ x2', data=df_simul).fit()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 150
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Here we factor out the effect of x2\n",
"# Not really sure what the point of is this\n",
"plt.plot(r1.resid, r2.resid, 'o');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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OnTaz+cCPnHPtqXI/A1YAswlaCd92zv04W33P52iQWkSKlj4IHnXgux6VYpA6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\nZtqCogAAAABJRU5ErkJggg==\n",
"text": [
""
]
}
],
"prompt_number": 151
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So ultimately, if we use 'fertilitiy ~ agriculture' vs 'fertility ~ .', we get different signs for agriculture. So what is the better model? Well you can learn a lot more about this and learn Causal Inference, or you can ask 'how will people attack this model' and adjust accordingly"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### What if we include an unnecessary variable?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R -o swiss\n",
"data(swiss)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 152
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"swiss.columns = [_.replace('.', '_') for _ in swiss.columns]\n",
"swiss['z'] = swiss['Agriculture'] + swiss['Education']\n",
"y = 'Fertility'\n",
"x = \"+\".join(swiss.columns - [y])\n",
"formula = '%s ~ %s' % (y, x)\n",
"swiss.head()\n",
"x\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 153,
"text": [
"'Agriculture+Catholic+Education+Examination+Infant_Mortality+z'"
]
}
],
"prompt_number": 153
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"r = sm.ols('%s ~ %s' % (y, x), data=swiss).fit();"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 154
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# wait, this doesn't work. sm.ols doesn't pick up that Z is no good\n",
"r.summary()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"OLS Regression Results \n",
"\n",
" Dep. Variable: Fertility R-squared: 0.707 \n",
" \n",
"\n",
" Model: OLS Adj. R-squared: 0.671 \n",
" \n",
"\n",
" Method: Least Squares F-statistic: 19.76 \n",
" \n",
"\n",
" Date: Tue, 30 Sep 2014 Prob (F-statistic): 5.59e-10 \n",
" \n",
"\n",
" Time: 15:48:49 Log-Likelihood: -156.04 \n",
" \n",
"\n",
" No. Observations: 47 AIC: 324.1 \n",
" \n",
"\n",
" Df Residuals: 41 BIC: 335.2 \n",
" \n",
"\n",
" Df Model: 5 \n",
" \n",
"
\n",
"\n",
"\n",
" coef std err t P>|t| [95.0% Conf. Int.] \n",
" \n",
"\n",
" Intercept 66.9152 10.706 6.250 0.000 45.294 88.536 \n",
" \n",
"\n",
" Agriculture 0.1756 0.062 2.852 0.007 0.051 0.300 \n",
" \n",
"\n",
" Catholic 0.1041 0.035 2.953 0.005 0.033 0.175 \n",
" \n",
"\n",
" Education -0.5233 0.115 -4.536 0.000 -0.756 -0.290 \n",
" \n",
"\n",
" Examination -0.2580 0.254 -1.016 0.315 -0.771 0.255 \n",
" \n",
"\n",
" Infant_Mortality 1.0770 0.382 2.822 0.007 0.306 1.848 \n",
" \n",
"\n",
" z -0.3477 0.073 -4.760 0.000 -0.495 -0.200 \n",
" \n",
"
\n",
"\n",
"\n",
" Omnibus: 0.058 Durbin-Watson: 1.454 \n",
" \n",
"\n",
" Prob(Omnibus): 0.971 Jarque-Bera (JB): 0.155 \n",
" \n",
"\n",
" Skew: -0.077 Prob(JB): 0.925 \n",
" \n",
"\n",
" Kurtosis: 2.764 Cond. No. 1.11e+08 \n",
" \n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 155,
"text": [
"\n",
"\"\"\"\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: Fertility R-squared: 0.707\n",
"Model: OLS Adj. R-squared: 0.671\n",
"Method: Least Squares F-statistic: 19.76\n",
"Date: Tue, 30 Sep 2014 Prob (F-statistic): 5.59e-10\n",
"Time: 15:48:49 Log-Likelihood: -156.04\n",
"No. Observations: 47 AIC: 324.1\n",
"Df Residuals: 41 BIC: 335.2\n",
"Df Model: 5 \n",
"====================================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"------------------------------------------------------------------------------------\n",
"Intercept 66.9152 10.706 6.250 0.000 45.294 88.536\n",
"Agriculture 0.1756 0.062 2.852 0.007 0.051 0.300\n",
"Catholic 0.1041 0.035 2.953 0.005 0.033 0.175\n",
"Education -0.5233 0.115 -4.536 0.000 -0.756 -0.290\n",
"Examination -0.2580 0.254 -1.016 0.315 -0.771 0.255\n",
"Infant_Mortality 1.0770 0.382 2.822 0.007 0.306 1.848\n",
"z -0.3477 0.073 -4.760 0.000 -0.495 -0.200\n",
"==============================================================================\n",
"Omnibus: 0.058 Durbin-Watson: 1.454\n",
"Prob(Omnibus): 0.971 Jarque-Bera (JB): 0.155\n",
"Skew: -0.077 Prob(JB): 0.925\n",
"Kurtosis: 2.764 Cond. No. 1.11e+08\n",
"==============================================================================\n",
"\n",
"Warnings:\n",
"[1] The smallest eigenvalue is 3.87e-11. This might indicate that there are\n",
"strong multicollinearity problems or that the design matrix is singular.\n",
"\"\"\""
]
}
],
"prompt_number": 155
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"# R does pick up that Z is no good. Note that the agriculture value is different\n",
"# Post question about this\n",
"data(swiss)\n",
"z<-swiss$Agriculture+swiss$Education\n",
"lm(Fertility~.+z,data=swiss)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"\n",
"Call:\n",
"lm(formula = Fertility ~ . + z, data = swiss)\n",
"\n",
"Coefficients:\n",
" (Intercept) Agriculture Examination Education Catholic \n",
" 66.9152 -0.1721 -0.2580 -0.8709 0.1041 \n",
"Infant.Mortality z \n",
" 1.0770 NA \n",
"\n"
]
}
],
"prompt_number": 156
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" \n",
"## Dummy Variables"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Dummy variables are smart\n",
"* Consider the linear model\n",
"$$\n",
"Y_i = \\beta_0 + X_{i1} \\beta_1 + \\epsilon_{i}\n",
"$$\n",
"where each $X_{i1}$ is binary so that it is a 1 if measurement $i$ is in a group and 0 otherwise. (Treated versus not in a clinical trial, for example.)\n",
"* Then for people in the group $E[Y_i] = \\beta_0 + \\beta_1$\n",
"* And for people not in the group $E[Y_i] = \\beta_0$\n",
"* The LS fits work out to be $\\hat \\beta_0 + \\hat \\beta_1$ is the mean for those in the group and $\\hat \\beta_0$ is the mean for those not in the group.\n",
"* $\\beta_1$ is interpretted as the increase or decrease in the mean comparing those in the group to those not.\n",
"* Note including a binary variable that is 1 for those not in the group would be redundant. It would create three parameters to describe two means."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### More than 2 levels\n",
"* Consider a multilevel factor level. For didactic reasons, let's say a three level factor (example, US political party affiliation: Republican, Democrat, Independent)\n",
"* $Y_i = \\beta_0 + X_{i1} \\beta_1 + X_{i2} \\beta_2 + \\epsilon_i$.\n",
"* $X_{i1}$ is 1 for Republicans and 0 otherwise.\n",
"* $X_{i2}$ is 1 for Democrats and 0 otherwise.\n",
"* If $i$ is Republican $E[Y_i] = \\beta_0 +\\beta_1$\n",
"* If $i$ is Democrat $E[Y_i] = \\beta_0 + \\beta_2$.\n",
"* If $i$ is Independent $E[Y_i] = \\beta_0$.\n",
"* $\\beta_1$ compares Republicans to Independents.\n",
"* $\\beta_2$ compares Democrats to Independents.\n",
"* $\\beta_1 - \\beta_2$ compares Republicans to Democrats.\n",
"* (Choice of reference category changes the interpretation.)"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R -o InsectSprays\n",
"require(ggplot)\n",
"g <- ggplot(InsectSprays, aes(spray, count)) + geom_boxplot()\n",
"#summary(lm(count ~ spray, data = InsectSprays))$coef\n",
"print(g)\n",
"summary(lm(count ~ spray, data = InsectSprays))$coef"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"Loading required package: ggplot\n",
" Estimate Std. Error t value Pr(>|t|)\n",
"(Intercept) 14.5000000 1.132156 12.8074279 1.470512e-19\n",
"sprayB 0.8333333 1.601110 0.5204724 6.044761e-01\n",
"sprayC -12.4166667 1.601110 -7.7550382 7.266893e-11\n",
"sprayD -9.5833333 1.601110 -5.9854322 9.816910e-08\n",
"sprayE -11.0000000 1.601110 -6.8702352 2.753922e-09\n",
"sprayF 2.1666667 1.601110 1.3532281 1.805998e-01\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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NGiV6S04bN24U3Us2/Z2y1md6jUnToH8mHZI/g24vDutPWiR/xqHmoGtUCzzaK8fFxLZx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\nP0/9ONWUhApYAAAAAElFTkSuQmCC\n"
}
],
"prompt_number": 157
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# InsectSprays['spray'].astype(str)\n",
"results = sm.ols(\"count ~ spray\", data = InsectSprays).fit()\n",
"results.summary()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"OLS Regression Results \n",
"\n",
" Dep. Variable: count R-squared: 0.724 \n",
" \n",
"\n",
" Model: OLS Adj. R-squared: 0.704 \n",
" \n",
"\n",
" Method: Least Squares F-statistic: 34.70 \n",
" \n",
"\n",
" Date: Tue, 30 Sep 2014 Prob (F-statistic): 3.18e-17 \n",
" \n",
"\n",
" Time: 15:48:49 Log-Likelihood: -197.42 \n",
" \n",
"\n",
" No. Observations: 72 AIC: 406.8 \n",
" \n",
"\n",
" Df Residuals: 66 BIC: 420.5 \n",
" \n",
"\n",
" Df Model: 5 \n",
" \n",
"
\n",
"\n",
"\n",
" coef std err t P>|t| [95.0% Conf. Int.] \n",
" \n",
"\n",
" Intercept 14.5000 1.132 12.807 0.000 12.240 16.760 \n",
" \n",
"\n",
" spray[T.B] 0.8333 1.601 0.520 0.604 -2.363 4.030 \n",
" \n",
"\n",
" spray[T.C] -12.4167 1.601 -7.755 0.000 -15.613 -9.220 \n",
" \n",
"\n",
" spray[T.D] -9.5833 1.601 -5.985 0.000 -12.780 -6.387 \n",
" \n",
"\n",
" spray[T.E] -11.0000 1.601 -6.870 0.000 -14.197 -7.803 \n",
" \n",
"\n",
" spray[T.F] 2.1667 1.601 1.353 0.181 -1.030 5.363 \n",
" \n",
"
\n",
"\n",
"\n",
" Omnibus: 3.201 Durbin-Watson: 1.753 \n",
" \n",
"\n",
" Prob(Omnibus): 0.202 Jarque-Bera (JB): 2.421 \n",
" \n",
"\n",
" Skew: 0.411 Prob(JB): 0.298 \n",
" \n",
"\n",
" Kurtosis: 3.360 Cond. No. 6.85 \n",
" \n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 158,
"text": [
"\n",
"\"\"\"\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: count R-squared: 0.724\n",
"Model: OLS Adj. R-squared: 0.704\n",
"Method: Least Squares F-statistic: 34.70\n",
"Date: Tue, 30 Sep 2014 Prob (F-statistic): 3.18e-17\n",
"Time: 15:48:49 Log-Likelihood: -197.42\n",
"No. Observations: 72 AIC: 406.8\n",
"Df Residuals: 66 BIC: 420.5\n",
"Df Model: 5 \n",
"==============================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"------------------------------------------------------------------------------\n",
"Intercept 14.5000 1.132 12.807 0.000 12.240 16.760\n",
"spray[T.B] 0.8333 1.601 0.520 0.604 -2.363 4.030\n",
"spray[T.C] -12.4167 1.601 -7.755 0.000 -15.613 -9.220\n",
"spray[T.D] -9.5833 1.601 -5.985 0.000 -12.780 -6.387\n",
"spray[T.E] -11.0000 1.601 -6.870 0.000 -14.197 -7.803\n",
"spray[T.F] 2.1667 1.601 1.353 0.181 -1.030 5.363\n",
"==============================================================================\n",
"Omnibus: 3.201 Durbin-Watson: 1.753\n",
"Prob(Omnibus): 0.202 Jarque-Bera (JB): 2.421\n",
"Skew: 0.411 Prob(JB): 0.298\n",
"Kurtosis: 3.360 Cond. No. 6.85\n",
"==============================================================================\n",
"\"\"\""
]
}
],
"prompt_number": 158
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"### Hard coding the dummy variables"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 159
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"summary(lm(count~ I(1*(spray=='B'))+I(1*(spray=='C'))+\n",
"I(1*(spray=='D'))+I(1*(spray=='E'))+\n",
"I(1*(spray=='F')) ,data=InsectSprays))$coef"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
" Estimate Std. Error t value Pr(>|t|)\n",
"(Intercept) 14.5000000 1.132156 12.8074279 1.470512e-19\n",
"I(1 * (spray == \"B\")) 0.8333333 1.601110 0.5204724 6.044761e-01\n",
"I(1 * (spray == \"C\")) -12.4166667 1.601110 -7.7550382 7.266893e-11\n",
"I(1 * (spray == \"D\")) -9.5833333 1.601110 -5.9854322 9.816910e-08\n",
"I(1 * (spray == \"E\")) -11.0000000 1.601110 -6.8702352 2.753922e-09\n",
"I(1 * (spray == \"F\")) 2.1666667 1.601110 1.3532281 1.805998e-01\n"
]
}
],
"prompt_number": 160
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"formula = \"count~ I(1*(spray=='B'))+I(1*(spray=='C'))+I(1*(spray=='D'))+I(1*(spray=='E'))+I(1*(spray=='F'))\""
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 161
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"formula"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 162,
"text": [
"\"count~ I(1*(spray=='B'))+I(1*(spray=='C'))+I(1*(spray=='D'))+I(1*(spray=='E'))+I(1*(spray=='F'))\""
]
}
],
"prompt_number": 162
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sm.ols(formula, data=InsectSprays).fit().summary()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"OLS Regression Results \n",
"\n",
" Dep. Variable: count R-squared: 0.724 \n",
" \n",
"\n",
" Model: OLS Adj. R-squared: 0.704 \n",
" \n",
"\n",
" Method: Least Squares F-statistic: 34.70 \n",
" \n",
"\n",
" Date: Tue, 30 Sep 2014 Prob (F-statistic): 3.18e-17 \n",
" \n",
"\n",
" Time: 15:48:49 Log-Likelihood: -197.42 \n",
" \n",
"\n",
" No. Observations: 72 AIC: 406.8 \n",
" \n",
"\n",
" Df Residuals: 66 BIC: 420.5 \n",
" \n",
"\n",
" Df Model: 5 \n",
" \n",
"
\n",
"\n",
"\n",
" coef std err t P>|t| [95.0% Conf. Int.] \n",
" \n",
"\n",
" Intercept 14.5000 1.132 12.807 0.000 12.240 16.760 \n",
" \n",
"\n",
" I(1 * (spray == 'B')) 0.8333 1.601 0.520 0.604 -2.363 4.030 \n",
" \n",
"\n",
" I(1 * (spray == 'C')) -12.4167 1.601 -7.755 0.000 -15.613 -9.220 \n",
" \n",
"\n",
" I(1 * (spray == 'D')) -9.5833 1.601 -5.985 0.000 -12.780 -6.387 \n",
" \n",
"\n",
" I(1 * (spray == 'E')) -11.0000 1.601 -6.870 0.000 -14.197 -7.803 \n",
" \n",
"\n",
" I(1 * (spray == 'F')) 2.1667 1.601 1.353 0.181 -1.030 5.363 \n",
" \n",
"
\n",
"\n",
"\n",
" Omnibus: 3.201 Durbin-Watson: 1.753 \n",
" \n",
"\n",
" Prob(Omnibus): 0.202 Jarque-Bera (JB): 2.421 \n",
" \n",
"\n",
" Skew: 0.411 Prob(JB): 0.298 \n",
" \n",
"\n",
" Kurtosis: 3.360 Cond. No. 6.85 \n",
" \n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 163,
"text": [
"\n",
"\"\"\"\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: count R-squared: 0.724\n",
"Model: OLS Adj. R-squared: 0.704\n",
"Method: Least Squares F-statistic: 34.70\n",
"Date: Tue, 30 Sep 2014 Prob (F-statistic): 3.18e-17\n",
"Time: 15:48:49 Log-Likelihood: -197.42\n",
"No. Observations: 72 AIC: 406.8\n",
"Df Residuals: 66 BIC: 420.5\n",
"Df Model: 5 \n",
"=========================================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"-----------------------------------------------------------------------------------------\n",
"Intercept 14.5000 1.132 12.807 0.000 12.240 16.760\n",
"I(1 * (spray == 'B')) 0.8333 1.601 0.520 0.604 -2.363 4.030\n",
"I(1 * (spray == 'C')) -12.4167 1.601 -7.755 0.000 -15.613 -9.220\n",
"I(1 * (spray == 'D')) -9.5833 1.601 -5.985 0.000 -12.780 -6.387\n",
"I(1 * (spray == 'E')) -11.0000 1.601 -6.870 0.000 -14.197 -7.803\n",
"I(1 * (spray == 'F')) 2.1667 1.601 1.353 0.181 -1.030 5.363\n",
"==============================================================================\n",
"Omnibus: 3.201 Durbin-Watson: 1.753\n",
"Prob(Omnibus): 0.202 Jarque-Bera (JB): 2.421\n",
"Skew: 0.411 Prob(JB): 0.298\n",
"Kurtosis: 3.360 Cond. No. 6.85\n",
"==============================================================================\n",
"\"\"\""
]
}
],
"prompt_number": 163
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### What if we include all 6?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"lm(count~\n",
"I(1*(spray=='B'))+I(1*(spray=='C'))+ I(1*(spray=='D'))+I(1*(spray=='E'))+ I(1*(spray=='F'))+I(1*(spray=='A')),data=InsectSprays)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"\n",
"Call:\n",
"lm(formula = count ~ I(1 * (spray == \"B\")) + I(1 * (spray == \n",
" \"C\")) + I(1 * (spray == \"D\")) + I(1 * (spray == \"E\")) + I(1 * \n",
" (spray == \"F\")) + I(1 * (spray == \"A\")), data = InsectSprays)\n",
"\n",
"Coefficients:\n",
" (Intercept) I(1 * (spray == \"B\")) I(1 * (spray == \"C\")) I(1 * (spray == \"D\")) \n",
" 14.5000 0.8333 -12.4167 -9.5833 \n",
"I(1 * (spray == \"E\")) I(1 * (spray == \"F\")) I(1 * (spray == \"A\")) \n",
" -11.0000 2.1667 NA \n",
"\n"
]
}
],
"prompt_number": 164
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"formula=\"count~I(1*(spray=='B'))+I(1*(spray=='C'))+ I(1*(spray=='D'))+I(1*(spray=='E'))+ I(1*(spray=='F'))+I(1*(spray=='A'))\"\n",
"sm.ols(formula, data=InsectSprays).fit().summary()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"OLS Regression Results \n",
"\n",
" Dep. Variable: count R-squared: 0.724 \n",
" \n",
"\n",
" Model: OLS Adj. R-squared: 0.704 \n",
" \n",
"\n",
" Method: Least Squares F-statistic: 34.70 \n",
" \n",
"\n",
" Date: Tue, 30 Sep 2014 Prob (F-statistic): 3.18e-17 \n",
" \n",
"\n",
" Time: 15:48:50 Log-Likelihood: -197.42 \n",
" \n",
"\n",
" No. Observations: 72 AIC: 406.8 \n",
" \n",
"\n",
" Df Residuals: 66 BIC: 420.5 \n",
" \n",
"\n",
" Df Model: 5 \n",
" \n",
"
\n",
"\n",
"\n",
" coef std err t P>|t| [95.0% Conf. Int.] \n",
" \n",
"\n",
" Intercept 8.1429 0.396 20.554 0.000 7.352 8.934 \n",
" \n",
"\n",
" I(1 * (spray == 'B')) 7.1905 1.036 6.943 0.000 5.123 9.258 \n",
" \n",
"\n",
" I(1 * (spray == 'C')) -6.0595 1.036 -5.851 0.000 -8.127 -3.992 \n",
" \n",
"\n",
" I(1 * (spray == 'D')) -3.2262 1.036 -3.115 0.003 -5.294 -1.159 \n",
" \n",
"\n",
" I(1 * (spray == 'E')) -4.6429 1.036 -4.483 0.000 -6.711 -2.575 \n",
" \n",
"\n",
" I(1 * (spray == 'F')) 8.5238 1.036 8.231 0.000 6.456 10.591 \n",
" \n",
"\n",
" I(1 * (spray == 'A')) 6.3571 1.036 6.138 0.000 4.289 8.425 \n",
" \n",
"
\n",
"\n",
"\n",
" Omnibus: 3.201 Durbin-Watson: 1.753 \n",
" \n",
"\n",
" Prob(Omnibus): 0.202 Jarque-Bera (JB): 2.421 \n",
" \n",
"\n",
" Skew: 0.411 Prob(JB): 0.298 \n",
" \n",
"\n",
" Kurtosis: 3.360 Cond. No. nan \n",
" \n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 165,
"text": [
"\n",
"\"\"\"\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: count R-squared: 0.724\n",
"Model: OLS Adj. R-squared: 0.704\n",
"Method: Least Squares F-statistic: 34.70\n",
"Date: Tue, 30 Sep 2014 Prob (F-statistic): 3.18e-17\n",
"Time: 15:48:50 Log-Likelihood: -197.42\n",
"No. Observations: 72 AIC: 406.8\n",
"Df Residuals: 66 BIC: 420.5\n",
"Df Model: 5 \n",
"=========================================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"-----------------------------------------------------------------------------------------\n",
"Intercept 8.1429 0.396 20.554 0.000 7.352 8.934\n",
"I(1 * (spray == 'B')) 7.1905 1.036 6.943 0.000 5.123 9.258\n",
"I(1 * (spray == 'C')) -6.0595 1.036 -5.851 0.000 -8.127 -3.992\n",
"I(1 * (spray == 'D')) -3.2262 1.036 -3.115 0.003 -5.294 -1.159\n",
"I(1 * (spray == 'E')) -4.6429 1.036 -4.483 0.000 -6.711 -2.575\n",
"I(1 * (spray == 'F')) 8.5238 1.036 8.231 0.000 6.456 10.591\n",
"I(1 * (spray == 'A')) 6.3571 1.036 6.138 0.000 4.289 8.425\n",
"==============================================================================\n",
"Omnibus: 3.201 Durbin-Watson: 1.753\n",
"Prob(Omnibus): 0.202 Jarque-Bera (JB): 2.421\n",
"Skew: 0.411 Prob(JB): 0.298\n",
"Kurtosis: 3.360 Cond. No. nan\n",
"==============================================================================\n",
"\n",
"Warnings:\n",
"[1] The smallest eigenvalue is -1.78e-15. This might indicate that there are\n",
"strong multicollinearity problems or that the design matrix is singular.\n",
"\"\"\""
]
}
],
"prompt_number": 165
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### My Python version doesnt give the ```NA``` like R does when duplicative information is provided"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### What if we omit the intercept?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"formula = \"count~ I(1*(spray=='B'))+I(1*(spray=='C'))+I(1*(spray=='D'))+I(1*(spray=='E'))+I(1*(spray=='F')) -1\""
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 166
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sm.ols(formula, data=InsectSprays).fit().summary()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"OLS Regression Results \n",
"\n",
" Dep. Variable: count R-squared: 0.653 \n",
" \n",
"\n",
" Model: OLS Adj. R-squared: 0.627 \n",
" \n",
"\n",
" Method: Least Squares F-statistic: 25.16 \n",
" \n",
"\n",
" Date: Tue, 30 Sep 2014 Prob (F-statistic): 3.48e-14 \n",
" \n",
"\n",
" Time: 15:48:50 Log-Likelihood: -242.37 \n",
" \n",
"\n",
" No. Observations: 72 AIC: 494.7 \n",
" \n",
"\n",
" Df Residuals: 67 BIC: 506.1 \n",
" \n",
"\n",
" Df Model: 5 \n",
" \n",
"
\n",
"\n",
"\n",
" coef std err t P>|t| [95.0% Conf. Int.] \n",
" \n",
"\n",
" I(1 * (spray == 'B')) 15.3333 2.098 7.309 0.000 11.146 19.521 \n",
" \n",
"\n",
" I(1 * (spray == 'C')) 2.0833 2.098 0.993 0.324 -2.104 6.271 \n",
" \n",
"\n",
" I(1 * (spray == 'D')) 4.9167 2.098 2.344 0.022 0.729 9.104 \n",
" \n",
"\n",
" I(1 * (spray == 'E')) 3.5000 2.098 1.668 0.100 -0.687 7.687 \n",
" \n",
"\n",
" I(1 * (spray == 'F')) 16.6667 2.098 7.945 0.000 12.479 20.854 \n",
" \n",
"
\n",
"\n",
"\n",
" Omnibus: 18.081 Durbin-Watson: 0.586 \n",
" \n",
"\n",
" Prob(Omnibus): 0.000 Jarque-Bera (JB): 21.653 \n",
" \n",
"\n",
" Skew: 1.228 Prob(JB): 1.99e-05 \n",
" \n",
"\n",
" Kurtosis: 4.090 Cond. No. 1.00 \n",
" \n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 167,
"text": [
"\n",
"\"\"\"\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: count R-squared: 0.653\n",
"Model: OLS Adj. R-squared: 0.627\n",
"Method: Least Squares F-statistic: 25.16\n",
"Date: Tue, 30 Sep 2014 Prob (F-statistic): 3.48e-14\n",
"Time: 15:48:50 Log-Likelihood: -242.37\n",
"No. Observations: 72 AIC: 494.7\n",
"Df Residuals: 67 BIC: 506.1\n",
"Df Model: 5 \n",
"=========================================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"-----------------------------------------------------------------------------------------\n",
"I(1 * (spray == 'B')) 15.3333 2.098 7.309 0.000 11.146 19.521\n",
"I(1 * (spray == 'C')) 2.0833 2.098 0.993 0.324 -2.104 6.271\n",
"I(1 * (spray == 'D')) 4.9167 2.098 2.344 0.022 0.729 9.104\n",
"I(1 * (spray == 'E')) 3.5000 2.098 1.668 0.100 -0.687 7.687\n",
"I(1 * (spray == 'F')) 16.6667 2.098 7.945 0.000 12.479 20.854\n",
"==============================================================================\n",
"Omnibus: 18.081 Durbin-Watson: 0.586\n",
"Prob(Omnibus): 0.000 Jarque-Bera (JB): 21.653\n",
"Skew: 1.228 Prob(JB): 1.99e-05\n",
"Kurtosis: 4.090 Cond. No. 1.00\n",
"==============================================================================\n",
"\"\"\""
]
}
],
"prompt_number": 167
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"InsectSprays.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"
\n",
" \n",
" \n",
" \n",
" count \n",
" spray \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" 10 \n",
" A \n",
" \n",
" \n",
" 1 \n",
" 7 \n",
" A \n",
" \n",
" \n",
" 2 \n",
" 20 \n",
" A \n",
" \n",
" \n",
" 3 \n",
" 14 \n",
" A \n",
" \n",
" \n",
" 4 \n",
" 14 \n",
" A \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 168,
"text": [
" count spray\n",
"0 10 A\n",
"1 7 A\n",
"2 20 A\n",
"3 14 A\n",
"4 14 A"
]
}
],
"prompt_number": 168
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"IS = InsectSprays\n",
"grouped = IS.groupby(\"spray\")"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 169
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"grouped.mean()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"
\n",
" \n",
" \n",
" \n",
" count \n",
" \n",
" \n",
" spray \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" A \n",
" 14.500000 \n",
" \n",
" \n",
" B \n",
" 15.333333 \n",
" \n",
" \n",
" C \n",
" 2.083333 \n",
" \n",
" \n",
" D \n",
" 4.916667 \n",
" \n",
" \n",
" E \n",
" 3.500000 \n",
" \n",
" \n",
" F \n",
" 16.666667 \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 170,
"text": [
" count\n",
"spray \n",
"A 14.500000\n",
"B 15.333333\n",
"C 2.083333\n",
"D 4.916667\n",
"E 3.500000\n",
"F 16.666667"
]
}
],
"prompt_number": 170
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Without the intercept we simply get the means"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" \n",
"## Interactions"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R -o hunger\n",
"hunger <- read.csv('data/hunger.csv')\n",
"hunger <- hunger[hunger$Sex != \"Both sexes\", ]\n",
"lm1 <- lm(hunger$Numeric ~ hunger$Year)\n",
"qqnorm(residuals(lm1))\n",
"qqline(residuals(lm1))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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M5e5lZ8y+oezbtWunaQ29CsVHG+cStI8+OHabBEggMAlgxlm1alX170W0KVge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\nAUgbUOD+l+7sAAAAAElFTkSuQmCC\n"
}
],
"prompt_number": 275
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"hunger.describe()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"
\n",
" \n",
" \n",
" \n",
" Year \n",
" Display.Value \n",
" Numeric \n",
" Low \n",
" High \n",
" Comments \n",
" \n",
" \n",
" \n",
" \n",
" count \n",
" 858.000000 \n",
" 858.000000 \n",
" 858.000000 \n",
" 858 \n",
" 858 \n",
" 858 \n",
" \n",
" \n",
" mean \n",
" 2000.466200 \n",
" 17.927389 \n",
" 17.927389 \n",
" -2147483648 \n",
" -2147483648 \n",
" -2147483648 \n",
" \n",
" \n",
" std \n",
" 6.819349 \n",
" 13.674090 \n",
" 13.674090 \n",
" 0 \n",
" 0 \n",
" 0 \n",
" \n",
" \n",
" min \n",
" 1970.000000 \n",
" 0.500000 \n",
" 0.500000 \n",
" -2147483648 \n",
" -2147483648 \n",
" -2147483648 \n",
" \n",
" \n",
" 25% \n",
" 1997.000000 \n",
" 6.000000 \n",
" 6.000000 \n",
" -2147483648 \n",
" -2147483648 \n",
" -2147483648 \n",
" \n",
" \n",
" 50% \n",
" 2001.000000 \n",
" 15.300000 \n",
" 15.300000 \n",
" -2147483648 \n",
" -2147483648 \n",
" -2147483648 \n",
" \n",
" \n",
" 75% \n",
" 2006.000000 \n",
" 25.500000 \n",
" 25.500000 \n",
" -2147483648 \n",
" -2147483648 \n",
" -2147483648 \n",
" \n",
" \n",
" max \n",
" 2011.000000 \n",
" 65.500000 \n",
" 65.500000 \n",
" -2147483648 \n",
" -2147483648 \n",
" -2147483648 \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 276,
"text": [
" Year Display.Value Numeric Low High \\\n",
"count 858.000000 858.000000 858.000000 858 858 \n",
"mean 2000.466200 17.927389 17.927389 -2147483648 -2147483648 \n",
"std 6.819349 13.674090 13.674090 0 0 \n",
"min 1970.000000 0.500000 0.500000 -2147483648 -2147483648 \n",
"25% 1997.000000 6.000000 6.000000 -2147483648 -2147483648 \n",
"50% 2001.000000 15.300000 15.300000 -2147483648 -2147483648 \n",
"75% 2006.000000 25.500000 25.500000 -2147483648 -2147483648 \n",
"max 2011.000000 65.500000 65.500000 -2147483648 -2147483648 \n",
"\n",
" Comments \n",
"count 858 \n",
"mean -2147483648 \n",
"std 0 \n",
"min -2147483648 \n",
"25% -2147483648 \n",
"50% -2147483648 \n",
"75% -2147483648 \n",
"max -2147483648 "
]
}
],
"prompt_number": 276
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# columns that need to be fixed from the R import of data\n",
"cols = ['Low', 'High', 'Comments']\n",
"\n",
"for col in cols:\n",
" hunger[col] = hunger[col].replace(-2147483648 , NaN)\n",
"hunger.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"
\n",
" \n",
" \n",
" \n",
" Indicator \n",
" Data.Source \n",
" PUBLISH.STATES \n",
" Year \n",
" WHO.region \n",
" Country \n",
" Sex \n",
" Display.Value \n",
" Numeric \n",
" Low \n",
" High \n",
" Comments \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" Children aged <5 years underweight (%) \n",
" NLIS_312819 \n",
" Published \n",
" 2004 \n",
" Eastern Mediterranean \n",
" Afghanistan \n",
" Female \n",
" 33.0 \n",
" 33.0 \n",
" NaN \n",
" NaN \n",
" NaN \n",
" \n",
" \n",
" 1 \n",
" Children aged <5 years underweight (%) \n",
" NLIS_312819 \n",
" Published \n",
" 2004 \n",
" Eastern Mediterranean \n",
" Afghanistan \n",
" Male \n",
" 32.7 \n",
" 32.7 \n",
" NaN \n",
" NaN \n",
" NaN \n",
" \n",
" \n",
" 2 \n",
" Children aged <5 years underweight (%) \n",
" NLIS_312361 \n",
" Published \n",
" 2000 \n",
" Europe \n",
" Albania \n",
" Male \n",
" 19.6 \n",
" 19.6 \n",
" NaN \n",
" NaN \n",
" NaN \n",
" \n",
" \n",
" 3 \n",
" Children aged <5 years underweight (%) \n",
" NLIS_312361 \n",
" Published \n",
" 2000 \n",
" Europe \n",
" Albania \n",
" Female \n",
" 14.2 \n",
" 14.2 \n",
" NaN \n",
" NaN \n",
" NaN \n",
" \n",
" \n",
" 4 \n",
" Children aged <5 years underweight (%) \n",
" NLIS_312879 \n",
" Published \n",
" 2005 \n",
" Europe \n",
" Albania \n",
" Male \n",
" 7.3 \n",
" 7.3 \n",
" NaN \n",
" NaN \n",
" NaN \n",
" \n",
" \n",
"
\n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 277,
"text": [
" Indicator Data.Source PUBLISH.STATES Year \\\n",
"0 Children aged <5 years underweight (%) NLIS_312819 Published 2004 \n",
"1 Children aged <5 years underweight (%) NLIS_312819 Published 2004 \n",
"2 Children aged <5 years underweight (%) NLIS_312361 Published 2000 \n",
"3 Children aged <5 years underweight (%) NLIS_312361 Published 2000 \n",
"4 Children aged <5 years underweight (%) NLIS_312879 Published 2005 \n",
"\n",
" WHO.region Country Sex Display.Value Numeric Low \\\n",
"0 Eastern Mediterranean Afghanistan Female 33.0 33.0 NaN \n",
"1 Eastern Mediterranean Afghanistan Male 32.7 32.7 NaN \n",
"2 Europe Albania Male 19.6 19.6 NaN \n",
"3 Europe Albania Female 14.2 14.2 NaN \n",
"4 Europe Albania Male 7.3 7.3 NaN \n",
"\n",
" High Comments \n",
"0 NaN NaN \n",
"1 NaN NaN \n",
"2 NaN NaN \n",
"3 NaN NaN \n",
"4 NaN NaN "
]
}
],
"prompt_number": 277
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"y = 'Numeric'\n",
"x = 'Year'\n",
"formula = '%s ~ %s' %(y, x,)\n",
"fit = sm.ols(formula, data=hunger).fit() "
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 278
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fit.summary()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
"OLS Regression Results \n",
"\n",
" Dep. Variable: Numeric R-squared: 0.018 \n",
" \n",
"\n",
" Model: OLS Adj. R-squared: 0.017 \n",
" \n",
"\n",
" Method: Least Squares F-statistic: 15.43 \n",
" \n",
"\n",
" Date: Tue, 30 Sep 2014 Prob (F-statistic): 9.26e-05 \n",
" \n",
"\n",
" Time: 21:04:21 Log-Likelihood: -3453.4 \n",
" \n",
"\n",
" No. Observations: 858 AIC: 6911. \n",
" \n",
"\n",
" Df Residuals: 856 BIC: 6920. \n",
" \n",
"\n",
" Df Model: 1 \n",
" \n",
"
\n",
"\n",
"\n",
" coef std err t P>|t| [95.0% Conf. Int.] \n",
" \n",
"\n",
" Intercept 551.6586 135.886 4.060 0.000 284.951 818.367 \n",
" \n",
"\n",
" Year -0.2668 0.068 -3.928 0.000 -0.400 -0.133 \n",
" \n",
"
\n",
"\n",
"\n",
" Omnibus: 82.684 Durbin-Watson: 0.298 \n",
" \n",
"\n",
" Prob(Omnibus): 0.000 Jarque-Bera (JB): 105.636 \n",
" \n",
"\n",
" Skew: 0.855 Prob(JB): 1.15e-23 \n",
" \n",
"\n",
" Kurtosis: 3.165 Cond. No. 5.87e+05 \n",
" \n",
"
"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 279,
"text": [
"\n",
"\"\"\"\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: Numeric R-squared: 0.018\n",
"Model: OLS Adj. R-squared: 0.017\n",
"Method: Least Squares F-statistic: 15.43\n",
"Date: Tue, 30 Sep 2014 Prob (F-statistic): 9.26e-05\n",
"Time: 21:04:21 Log-Likelihood: -3453.4\n",
"No. Observations: 858 AIC: 6911.\n",
"Df Residuals: 856 BIC: 6920.\n",
"Df Model: 1 \n",
"==============================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"------------------------------------------------------------------------------\n",
"Intercept 551.6586 135.886 4.060 0.000 284.951 818.367\n",
"Year -0.2668 0.068 -3.928 0.000 -0.400 -0.133\n",
"==============================================================================\n",
"Omnibus: 82.684 Durbin-Watson: 0.298\n",
"Prob(Omnibus): 0.000 Jarque-Bera (JB): 105.636\n",
"Skew: 0.855 Prob(JB): 1.15e-23\n",
"Kurtosis: 3.165 Cond. No. 5.87e+05\n",
"==============================================================================\n",
"\n",
"Warnings:\n",
"[1] The condition number is large, 5.87e+05. This might indicate that there are\n",
"strong multicollinearity or other numerical problems.\n",
"\"\"\""
]
}
],
"prompt_number": 279
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig, ax = plt.subplots(figsize=(12, 8))\n",
"graphics.plot_regress_exog(fit, \"Year\", fig);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
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I+X4MNOD0lERq/6+AN4CXRGSPiMyV6GNo9CS3i/Q5H/W1gbiu22eqWhfteKbrseDHdFbL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PAAAg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ffmPGjBl06dIFgEceecTgqISonRyZfEDFexc4YjHOb745XSzxATCZ3mLXrphqH7u2q031c0UY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\noQhDQUGB3dMoDPH8D22lqDUcHeFYCMU0PW/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6KSVrskf/+lcJr712ipqaNgGEPXsamTHD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gkhnkbR3c4F3tBdFGz8OHBw+kgmFqWTU6eS0LnW29qe0p5vN+HZyWa6XI9rPQ1GlutQZGRY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\nhAoes6mnASFus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"text": [
""
]
}
],
"prompt_number": 280
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Remember the linear model\n",
"$$Hu_i = b_0 + b_1 Y_i + e_i$$\n",
"\n",
"$b_0$ = percent hungry at Year 0 (*hasn't been calibrated to an interpretable value*)\n",
"\n",
"$b_1$ = decrease in percent hungry per year\n",
"\n",
"$e_i$ = everything we didn't measure\n",
"\n",
"Makes sense to subtract 1970 from all years"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"require(ggplot2)\n",
"g <- ggplot(hunger, aes(Year, Numeric, colour=Sex)) + geom_point(alpha=0.5)\n",
"g <- g + geom_smooth(method='lm', se=T)\n",
"g"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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m4UsqXrcFITNdsOfWQkLOdi/mib6Xen1vI6AM2Nv3R3unCEwMAnDAitVGx9OR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OCZTT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4yu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\nf2rutTSQHOgfAAAAAElFTkSuQmCC\n"
}
],
"prompt_number": 281
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Create one regression per gender, like the plot above\n",
"\n",
"$${HuF}_i = {bf}_0 + {bf}_1 {YF}_i + {ef}_i$$\n",
"\n",
"${bf}_0$ = percent of girls hungry at Year 0\n",
"\n",
"${bf}_1$ = decrease in percent of girls hungry per year\n",
"\n",
"${ef}_i$ = everything we didn't measure\n",
"\n",
"\n",
"$${HuM}_i = {bm}_0 + {bm}_1 {YM}_i + {em}_i$$\n",
"\n",
"${bm}_0$ = percent of boys hungry at Year 0\n",
"\n",
"${bm}_1$ = decrease in percent of boys hungry per year\n",
"\n",
"${em}_i$ = everything we didn't measure"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Two lines, two slopes"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"lmM <- lm(hunger$Numeric[hunger$Sex==\"Male\"] ~ hunger$Year[hunger$Sex==\"Male\"])\n",
"lmF <- lm(hunger$Numeric[hunger$Sex==\"Female\"] ~ hunger$Year[hunger$Sex==\"Female\"])\n",
"print(summary(lmM))\n",
"plot(hunger$Year,hunger$Numeric,pch=19)\n",
"points(hunger$Year,hunger$Numeric,pch=19,col=((hunger$Sex==\"Male\")*1+1))\n",
"lines(hunger$Year[hunger$Sex==\"Male\"],lmM$fitted,col=\"black\",lwd=3)\n",
"lines(hunger$Year[hunger$Sex==\"Female\"],lmF$fitted,col=\"red\",lwd=3)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"\n",
"Call:\n",
"lm(formula = hunger$Numeric[hunger$Sex == \"Male\"] ~ hunger$Year[hunger$Sex == \n",
" \"Male\"])\n",
"\n",
"Residuals:\n",
" Min 1Q Median 3Q Max \n",
"-25.092 -12.122 -1.717 8.249 42.226 \n",
"\n",
"Coefficients:\n",
" Estimate Std. Error t value Pr(>|t|) \n",
"(Intercept) 580.84512 195.50162 2.971 0.00314 **\n",
"hunger$Year[hunger$Sex == \"Male\"] -0.28091 0.09773 -2.874 0.00425 **\n",
"---\n",
"Signif. codes: 0 \u2018***\u2019 0.001 \u2018**\u2019 0.01 \u2018*\u2019 0.05 \u2018.\u2019 0.1 \u2018 \u2019 1\n",
"\n",
"Residual standard error: 13.8 on 427 degrees of freedom\n",
"Multiple R-squared: 0.01898,\tAdjusted R-squared: 0.01668 \n",
"F-statistic: 8.262 on 1 and 427 DF, p-value: 0.00425\n",
"\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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RCA7sDjVnvAvd9x2Adn/+BU5V/SD+9OkiDXzs2LHwwQcf6GW+iRcvQfCQYRDU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}
],
"prompt_number": 286
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Two lines, same slope\n",
"\n",
"$${Hu}_i = b_0 + b_1 \\mathbb{1}(Sex_i=\"Male\") + b_2 Y_i + e^*_i$$\n",
"\n",
"$b_0$ - percent hungry at year zero for females\n",
"\n",
"$b_0 + b_1$ - percent hungry at year zero for males\n",
"\n",
"$b_2$ - change in percent hungry (for either males or females) in one year\n",
"\n",
"$e^*_i$ - everything we didn't measure\n",
"\n",
"Males and Females both have slope $\\beta_2$\n",
"\n",
"Males have intercept $\\beta_0 + \\beta_1$\n",
"\n",
"Females have intercept $\\beta_0$"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"lmBoth <- lm(hunger$Numeric ~ hunger$Year + hunger$Sex)\n",
"print(summary(lmBoth))\n",
"plot(hunger$Year,hunger$Numeric,pch=19)\n",
"points(hunger$Year,hunger$Numeric,pch=19,col=((hunger$Sex==\"Male\")*1+1))\n",
"abline(c(lmBoth$coeff[1],lmBoth$coeff[2]),col=\"red\",lwd=3)\n",
"abline(c(lmBoth$coeff[1] + lmBoth$coeff[3],lmBoth$coeff[2] ),col=\"black\",lwd=3)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"\n",
"Call:\n",
"lm(formula = hunger$Numeric ~ hunger$Year + hunger$Sex)\n",
"\n",
"Residuals:\n",
" Min 1Q Median 3Q Max \n",
"-24.691 -11.556 -2.149 7.224 46.016 \n",
"\n",
"Coefficients:\n",
" Estimate Std. Error t value Pr(>|t|) \n",
"(Intercept) 550.68998 135.61772 4.061 5.34e-05 ***\n",
"hunger$Year -0.26680 0.06779 -3.936 8.97e-05 ***\n",
"hunger$SexMale 1.93730 0.92406 2.097 0.0363 * \n",
"---\n",
"Signif. codes: 0 \u2018***\u2019 0.001 \u2018**\u2019 0.01 \u2018*\u2019 0.05 \u2018.\u2019 0.1 \u2018 \u2019 1\n",
"\n",
"Residual standard error: 13.53 on 855 degrees of freedom\n",
"Multiple R-squared: 0.02273,\tAdjusted R-squared: 0.02044 \n",
"F-statistic: 9.942 on 2 and 855 DF, p-value: 5.39e-05\n",
"\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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RCA7sDjVnvAvd9x2Adn/+BU5V/SD+9OkiDXzs2LHwwQcf6GW+iRcvQfCQYRDU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Z2rx5szVx4kQrPDzcgphblYGRWmC0Fhis9fXXX1uFChVS+YsXL7aSJUtm9e7d2/r9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\nFFYAAAAASUVORK5CYII=\n"
}
],
"prompt_number": 283
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Two lines, different slopes (interactions)\n",
"\n",
"$${Hu}_i = b_0 + b_1 \\mathbb{1}(Sex_i=\"Male\") + b_2 Y_i + b_3 \\mathbb{1}(Sex_i=\"Male\")\\cdot Y_i + e^+ _i$$\n",
"\n",
"$b_0$ - percent hungry at year zero for females\n",
"\n",
"$b_0 + b_1$ - percent hungry at year zero for males\n",
"\n",
"$b_2$ - change in percent hungry (females) in one year\n",
"\n",
"$b_2 + b_3$ - change in percent hungry (males) in one year\n",
"\n",
"$e^+_i$ - everything we didn't measure\n",
"\n",
"$E[Hu_{male}] = \\beta_0 + \\beta_1 + \\beta_2Y + \\beta_3Y$\n",
"\n",
"$E[Hu_{female}] = \\beta_0 + \\beta_2Y$"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"lmBoth <- lm(hunger$Numeric ~ hunger$Year + hunger$Sex + hunger$Sex*hunger$Year)\n",
"print(summary(lmBoth))\n",
"plot(hunger$Year,hunger$Numeric,pch=19)\n",
"points(hunger$Year,hunger$Numeric,pch=19,col=((hunger$Sex==\"Male\")*1+1))\n",
"abline(c(lmBoth$coeff[1],lmBoth$coeff[2]),col=\"red\",lwd=3)\n",
"abline(c(lmBoth$coeff[1] + lmBoth$coeff[3],lmBoth$coeff[2] +lmBoth$coeff[4]),col=\"black\",lwd=3)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"\n",
"Call:\n",
"lm(formula = hunger$Numeric ~ hunger$Year + hunger$Sex + hunger$Sex * \n",
" hunger$Year)\n",
"\n",
"Residuals:\n",
" Min 1Q Median 3Q Max \n",
"-25.092 -11.613 -2.148 7.290 46.149 \n",
"\n",
"Coefficients:\n",
" Estimate Std. Error t value Pr(>|t|) \n",
"(Intercept) 522.47214 191.89871 2.723 0.00661 **\n",
"hunger$Year -0.25270 0.09593 -2.634 0.00858 **\n",
"hunger$SexMale 58.37299 271.38575 0.215 0.82975 \n",
"hunger$Year:hunger$SexMale -0.02821 0.13566 -0.208 0.83531 \n",
"---\n",
"Signif. codes: 0 \u2018***\u2019 0.001 \u2018**\u2019 0.01 \u2018*\u2019 0.05 \u2018.\u2019 0.1 \u2018 \u2019 1\n",
"\n",
"Residual standard error: 13.54 on 854 degrees of freedom\n",
"Multiple R-squared: 0.02278,\tAdjusted R-squared: 0.01934 \n",
"F-statistic: 6.635 on 3 and 854 DF, p-value: 0.0001969\n",
"\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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RCA7sDjVnvAvd9x2Adn/+BU5V/SD+9OkiDXzs2LHwwQcf6GW+iRcvQfCQYRDU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YyaCZ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LDylmbTkQFE0Zg0DiIVCxx4uJV7mpOWgQoGWxpZBgxkdRMEnLEKoUFAyYJuoeeeQR+eijj4TW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\nwlUZMuqrV69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}
],
"prompt_number": 285
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Interpretting a continuous interaction\n",
"$$\n",
"E[Y_i | X_{1i}=x_1, X_{2i}=x_2] = \\beta_0 + \\beta_1 x_{1} + \\beta_2 x_{2} + \\beta_3 x_{1}x_{2}\n",
"$$\n",
"\n",
"Holding $X_2$ constant we have\n",
"$$\n",
"E[Y_i | X_{1i}=x_1+1, X_{2i}=x_2]-E[Y_i | X_{1i}=x_1, X_{2i}=x_2]\n",
"= \\beta_1 + \\beta_3 x_{2}\n",
"$$\n",
"\n",
"And thus the expected change in $Y$ per unit change in $X_1$ holding all else constant is not constant. $\\beta_1$ is the slope when $x_{2} = 0$. \n",
"\n",
"Note further that:\n",
"$$\n",
"E[Y_i | X_{1i}=x_1+1, X_{2i}=x_2+1]-E[Y_i | X_{1i}=x_1, X_{2i}=x_2+1]\n",
"$$\n",
"$$\n",
"-E[Y_i | X_{1i}=x_1+1, X_{2i}=x_2]-E[Y_i | X_{1i}=x_1, X_{2i}=x_2]\n",
"$$\n",
"$$\n",
"=\\beta_3\n",
"$$\n",
"Thus, $\\beta_3$ is the change in the expected change in $Y$ per unit change in $X_1$, per unit change in $X_2$.\n",
"\n",
"Or, the change in the slope relating $X_1$ and $Y$ per unit change in $X_2$.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Example\n",
"\n",
"$$Hu_i = b_0 + b_1 In_i + b_2 Y_i + b_3 In_i \\times Y_i + e^+_i$$\n",
"\n",
"$b_0$ - percent hungry at year zero for children with whose parents have no income\n",
"\n",
"$b_1$ - change in percent hungry for each dollar of income in year zero\n",
"\n",
"$b_2$ - change in percent hungry in one year for children whose parents have no income\n",
"\n",
"$b_3$ - increased change in percent hungry by year for each dollar of income - e.g. if income is $10,000, then change in percent hungry in one year will be\n",
"\n",
"$$b_2 + 1e4 \\times b_3$$\n",
"\n",
"$e^+_i$ - everything we didn't measure\n",
"\n",
"__Lot's of care/caution needed!__\n",
"\n",
"__General Theme: Interactions are hard!__\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" \n",
"## Multivariate Regressions Simulations"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Fitting equation:\n",
" \n",
"$Y_i = \\beta_0 + \\beta_1X_i + \\beta_2t_i + \\epsilon_i$\n",
"\n",
"$t_i = \\begin{cases}\n",
"0\\\\\n",
"1\n",
"\\end{cases}$"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"n <- 100;\n",
"t <- rep(c(0, 1), c(n/2, n/2)); # treatment effect\n",
"x <- c(runif(n/2), runif(n/2)); # \n",
"\n",
"beta0 <- 0; #intercept\n",
"beta1 <- 2; #slope\n",
"tau <- 1; #treatment effect\n",
"sigma <- .2 # variance\n",
"\n",
"y <- beta0 + x * beta1 + t * tau + rnorm(n, sd = sigma) #simulate reg\n",
"plot(x, y, type = \"n\", frame = FALSE)\n",
"abline(lm(y ~ x), lwd = 2) # disregard treatment\n",
"abline(h = mean(y[1 : (n/2)]), lwd = 3) #mean untreated group\n",
"abline(h = mean(y[(n/2 + 1) : n]), lwd = 3) # mean treated gropu\n",
"fit <- lm(y ~ x + t) # correct model with treatment effect\n",
"\n",
"# The slope is simply x for both lines. When considering t, then the intersect is \\beta0 + t\n",
"\n",
"abline(coef(fit)[1], coef(fit)[2], lwd = 3)\n",
"abline(coef(fit)[1] + coef(fit)[3], coef(fit)[2], lwd = 3)\n",
"points(x[1 : (n/2)], y[1 : (n/2)], pch = 21, col = \"black\", bg = \"lightblue\", cex = 2)\n",
"points(x[(n/2 + 1) : n], y[(n/2 + 1) : n], pch = 21, col = \"black\", bg = \"salmon\", cex = 2)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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qx6t/TpMmDSySJscB/ycolUy7B/ZMygmdrUhRODo6qh+ufH7x4gWSJDBM3SSh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\nOHCg/cQgnhoUeS3p7Vrbtm2zn90cuQS5+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}
],
"prompt_number": 11
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Discussion\n",
"### Some things to note in this simulation\n",
"* The X variable is unrelated to group status\n",
"* The X variable is related to Y, but the intercept depends\n",
" on group status.\n",
"* The group variable is related to Y.\n",
" * The relationship between group status and Y is constant depending on X.\n",
" * The relationship between group and Y disregarding X is about the same as holding X constant"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"\n",
"n <- 100; t <- rep(c(0, 1), c(n/2, n/2)); x <- c(runif(n/2), 1.5 + runif(n/2));\n",
"beta0 <- 0; beta1 <- 2; tau <- 0; sigma <- .2\n",
"y <- beta0 + x * beta1 + t * tau + rnorm(n, sd = sigma)\n",
"plot(x, y, type = \"n\", frame = FALSE)\n",
"abline(lm(y ~ x), lwd = 2)\n",
"abline(h = mean(y[1 : (n/2)]), lwd = 3)\n",
"abline(h = mean(y[(n/2 + 1) : n]), lwd = 3)\n",
"fit <- lm(y ~ x + t)\n",
"abline(coef(fit)[1], coef(fit)[2], lwd = 3)\n",
"abline(coef(fit)[1] + coef(fit)[3], coef(fit)[2], lwd = 3)\n",
"points(x[1 : (n/2)], y[1 : (n/2)], pch = 21, col = \"black\", bg = \"lightblue\", cex = 2)\n",
"points(x[(n/2 + 1) : n], y[(n/2 + 1) : n], pch = 21, col = \"black\", bg = \"salmon\", cex = 2)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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J27Rp0/TWN8WLJqOADx06hKJFi6J+/fq4f/++BOi203ipTBU1atTIFLtWrVpB/emTFRKe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\nJCyB/wGN+FhCt5xpTQAAAABJRU5ErkJggg==\n"
}
],
"prompt_number": 12
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If you adjust for $x$, there is no difference\n",
"\n",
"If you look at the differences of the horizontal lines, which is the differences of the means, then the problem is that you are disregarding $x$, which could be a confounding regressor, and that's a problem\n",
"\n",
"ie - if you hold $x$ constant, there is almost no direct comparison\n",
"\n",
"The estimate of the differences is all $x$, no data"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from datetime import timedelta\n",
"YouTubeVideo('BhGQ4YCC8xA', start=int(timedelta(minutes=5, seconds=40).total_seconds()))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"\n",
" VIDEO \n",
" "
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 25,
"text": [
""
]
}
],
"prompt_number": 25
}
],
"metadata": {}
}
]
}