{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "([**Return to Week 2 index.**](http://localhost:8890/tree/Desktop/BIOM262/week02#))\n",
    "\n",
    "# Homework for Week 2\n",
    "\n",
    "## Table of Contents\n",
    "[**0. Statistical power and errors in hypothesis testing**](#0.-Statistical power and errors in hypothesis testing)  \n",
    "[**1. Simple linear regression**](#1.-Simple-linear-regression)  \n",
    "[**2. Non-linear relationship: particle decay**](#2.-Non-linear-relationships)  \n",
    "[**3. Non-linear regression**](#3.-Non-linear-regression)  \n",
    "[**4. Analysis of variance**](#4.-Analysis-of-variance)  \n",
    "[**5. ANCOVA**](#5.-ANCOVA)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* * *\n",
    "\n",
    "## 0. Statistical power and errors in hypothesis testing\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visit the app hosted on a ShinyIO hosted by UCSD Biostats<a href = \"https://ucsdbiostats.shinyapps.io/Lab_3_F2014/\"> here</a> to build your intuition about statistical power, sampling distributions, and hypothesis testing."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(End of Section 0. [Return to top.](#Table-of-Contents))\n",
    "\n",
    "* * *\n",
    "\n",
    "## 1. Simple linear regression\n",
    "**Load the data and look at it.**  This is data on plant growth and tannin content."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* * *\n",
    "\n",
    "## 1. Simple linear regression\n",
    "\n",
    "**Load the data and look at it.**  This is data on plant growth and tannin content."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>growth</th><th scope=col>tannin</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>12</td><td>0</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>10</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>8</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>11</td><td>3</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>6</td><td>4</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>7</td><td>5</td></tr>\n",
       "\t<tr><th scope=row>7</th><td>2</td><td>6</td></tr>\n",
       "\t<tr><th scope=row>8</th><td>3</td><td>7</td></tr>\n",
       "\t<tr><th scope=row>9</th><td>3</td><td>8</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       "  & growth & tannin\\\\\n",
       "\\hline\n",
       "\t1 & 12 & 0\\\\\n",
       "\t2 & 10 & 1\\\\\n",
       "\t3 & 8 & 2\\\\\n",
       "\t4 & 11 & 3\\\\\n",
       "\t5 & 6 & 4\\\\\n",
       "\t6 & 7 & 5\\\\\n",
       "\t7 & 2 & 6\\\\\n",
       "\t8 & 3 & 7\\\\\n",
       "\t9 & 3 & 8\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "  growth tannin\n",
       "1     12      0\n",
       "2     10      1\n",
       "3      8      2\n",
       "4     11      3\n",
       "5      6      4\n",
       "6      7      5\n",
       "7      2      6\n",
       "8      3      7\n",
       "9      3      8"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reg.data<-read.csv('shinyexample/tannin.csv')\n",
    "reg.data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Plot the data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(reg.data$tannin,reg.data$growth,pch=21,bg=\"blue\",asp=1,xlab=\"tannin content\",ylab=\"growth\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Make a simple linear model** where growth is a linear function of tannin.<br/>\n",
    "R syntax for models looks like response~explanatory.  lm() is a function to make a linear model.  In this case, the model is a regression line:  $growth_i = a+b*tannin_i$ where <i>a</i> is the intercept and <i>b</i> is the slope and <i>i</i> is a subscript indicating one individual in the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = growth ~ tannin, data = reg.data)\n",
       "\n",
       "Coefficients:\n",
       "(Intercept)       tannin  \n",
       "     11.756       -1.217  \n"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reg.model=lm(growth~tannin,data=reg.data)\n",
    "reg.model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Plot this line**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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qBGkaT8B8an5WVq6XzNV7jepowPaW+ovreWl1VOn5aXX9E9LGubjEbpzaczlW265MOPrMTEjK4y4m9Vjx5lL2z4fOfj3/ftpZ7bI8v38C03UhyUjSXOytQ4AAAQIECEybgIA0RWesjhx9Iy2/pJbNaQ9P295SR47qzfl1vdpelDbORUAap/Ycj3VI2x6QkaQNNSTlcXNGkn5jB5semgvy8u/r4/m3MzsczTyvIWn/jCRdd7ndDnbhZQIECBAgQIDA1Ar0KiBtPXnB1J6VHRRefym9a1r96/9RadekbW/5j7z4c2kZBSi5h2TRS50d8L5pK+e4pzvMcT2rjVHgnKa54LC2PTL/J/lC7kfaO+2DCUs/v75pvrVVGfcp5aYZJbrfDu5V2jurPzzfON7xm6VcXf+NWQgQIECAAAECBAh0QqAGl10tdRrw+oGxi1lumY3riNTlc2w1yNWRK5dgBaFrS0aOHjjrUrtvZzTpplvV+NRSbnvF9kePZkaR6j1JdeIGCwECBAgQIECgdwK9GkHq3dmZ0g49IXXXgFSHGiwdFEhAesqskPSJXEm3YlaZmRFx94wgXZFzOBOItn6sEzfU2e0sBAgQIECAAIHeCQhIvTulk++QgDT5c7DLChKQPjITkjKK9IZZG2Tkb+WFpbx4BwGpTtxQZ7dbkss3Zx3WUwIECBAgQIBAJwQEpE6chn4VISBNwfnM/Uh7Jhh9dSYk5dK742eV/ZDrJ2qoIWn2SFKduKHOblenALcQIECAAAECBHop0KuAlPvOe73U4HHjBfTw89nmCwvYbqGb1DrfnrZPWr1vydJRgcxsd3hmYvi3lHdQ2rWZuu6Xz2iafxmVm5C08s8TlPbNJynlkrrzc8/bD1dm9OitmUSxhqkdTRIy2twDAQIECBAgQGAqBWpAyh+Ey93Txvk79FRiTbror6aA/AV/3u2EMRdeA1Kt0z1IY4ZfyOEycnT3jCJdMxpJOq+Gpln7qRNt5J6kkokbymPSDk2zECBAgAABAgT6LNCrEaS+T/P9G/mXeFLa3dJOTXtn2lyWb81lJesMU2Bj03w+l9r9foZf67+nA/Md4fSEpLtnWvDMZFeuTPubYcroNQECBAgQIECAwDQI1M+m+WJaHfb7mY4WbASpoydmZ2UlJJ0wcz9SHt1jtDMs7xEgQIAAAQJ9FujVCFKfT9Tsvv1kvqgB6XOzX+zQcwGpQydjzqW07Y0SjP5hJiQlML1uzttakQABAgQIECDQH4FeBaS5fHBqH07dN9KJ56XVCRsW+yGwffDQh6UQaJotuXHsodnVt+vucsnd03N/0oOWYtf2QYAAAQIECBAgQGDIAkaQpvjsZwTpdmkX15GkjCJdnunA7zTF3VE6AQIECBAgQGC+AkaQ5itmfQJ9FljfNN/KSNLD0rZkFGmvlZm04eZte2Cf+6xvBAgQIECAAIG+CgzlEru+nj/96ojAhqapnwj7B6NyVmeu75NK2yYrWQgQIECAAAECBKZJQECaprOl1k4LZPrv1yQkvXFU5D3WlZIPiLUQIECAAAECBAhMk4CANE1nS62dF9hQyrMTkr40KvR3c1/SCztftAIJECBAgAABAgR+JCAg/YjCEwJLINA01+TTYo9OSDq77i2PJ6xu2/suwZ7tggABAgQIECBAYAwCAtIYkB1iWALnNc25CUZHpV2VSRtW5P9kHzm8bW81LAW9JUCAAAECBAhMp4CANJ3nTdUdF8j9SF9JiY+tZSYk7bciM9sd0Lb71q8tBAgQIECAAAEC3RUQkLp7blQ25QKZ2e5D6cJ1M9slJN1hn1I+mJnt8tRCgAABAgQIECDQVQEBqatnRl29EFhfyqtzqd1ptTNJRvdfW8rLe9ExnSBAgAABAgQI9FRAQOrpidWtjgg0TXt5KY9KSPpGrSgh6Q/WtO2TO1KdMggQIECAAAECBLYSEJC2AvElgaUWOL9pLktAOjLtB3Xf+T/dqzNpw12W+jj2R4AAAQIECBAgsHgBAWnxhvZAYJcCmbRhfVY6Nm1T2qpM2nBqQtIhu9zQCgQIECBAgAABAmMVEJDGyu1gQxbIpA2fzijSU6pBLrW7xW4JSWvbdo8hm+g7AQIECBAgQKBrAgJS186IenotkJD0toSkl406+XN5/Mted1jnCBAgQIAAAQJTJiAgTdkJU+70C2wo5Y8Skj5de5KRpEdmFGkmME1/5/SAAAECBAgQIDDlAgLSlJ9A5U+hQNNsujb3IyUkrR9V/5zVbfuAKeyJkgkQIECAAAECvRMQkHp3SnVoGgTObpofbMnMdqn1sowiNZm04f0JST8xDbWrkQABAgQIECDQZwEBqc9nV986LXBG09TPRqqfkZT/yr75P+PpCUn7dbpoxREgQIAAAQIEei4gIPX8BOtetwXWN81pSUczM9vdMv+HPLG0bQaULAQIECBAgAABApMQEJAmoe6YBGYJ5DOS3pKQ9KH6Ui63u8+6Ut4w621PCRAgQIAAAQIExiggII0R26EI7ETgsQlJXxm9f1xmtvuDnazrLQIECBAgQIAAgWUSEJCWCdZuCcxHIJ+PdNWmUo7KNufW7TKS9NLD2/ae89mHdQkQIECAAAECBBYvICAt3tAeCCyJwFlNc3ZGkY7Jzq5J2223Uk5a17ZrlmTndkKAAAECBAgQIDAnAQFpTkxWIjAegYwkfTFHesLoaAfk8fSD23bv8RzdUQgQIECAAAECBAQk/wYIdEwgM9u9NyW9cFTWHfcs5a86VqJyCBAgQIAAAQK9FRCQentqdWyaBdaX8qe53O7jtQ+5H+mYNW37xmnuj9oJECBAgAABAtMiICBNy5lS57AEmmbLJaU8LCHpW7Xj+T/qU3I/0kOGhaC3BAgQIECAAIHxCwhI4zd3RAJzEriwaS7JzHZHJiT9sG6Qx/dk+u8j5rSxlQgQIECAAAECBBYkICAtiM1GBMYjkJntvr2llIcmHG3JpXZ7pp2WSRsOGs/RHYUAAQIECBAgMDwBAWl451yPp0zgjKb5REp+5qjswzNpw8mlbXefsm4olwABAgQIECAwFQIC0lScJkUOXSDTf78ho0ivqw4ZRbr72lLeNnQT/SdAgAABAgQILIeAgLQcqvZJYBkENpTy3ISkz9ddJyQ9Lvcjvag+txAgQIAAAQIECCydgIC0dJb2RGB5BZrmmitLeWAOcuboQC/MzHa/trwHtXcCBAgQIECAwLAEBKRhnW+9nXKBc5vmvIwiHZV2ZUaRbpTHDx3WtreZ8m4pnwABAgQIECDQGQEBqTOnQiEE5iaQ+5H+IzPb/VZdOyHppruVcvp+bXuTuW1tLQIECBAgQIAAgZ0JCEg70/EegY4KZGa7ExOSjq/lJSTdLunog5nZzv+fO3q+lEWAAAECBAhMj4BfqKbnXKmUwA0ENjbNa3OJ3cn1xYSkX19XyqtusIIvCBAgQIAAAQIE5i0gIM2bzAYEuiOQSRsek2q+PqromZnZ7qndqU4lBAgQIECAAIHpExCQpu+cqZjAjwQyacPl+eKotAvqixlJelVC0i/U5xYCBAgQIECAAIH5CwhI8zezBYFOCaxvmo2bSnlQiro2bfeEpFMys92hnSpSMQQIECBAgACBKREQkKbkRCmTwM4Ezmyaz+b940brHJyZ7U5LSNpzZ9t4jwABAgQIECBAYFsBAWlbE68QmEqBjCT9RQp/aS0+o0h3Tkh611R2RNHjFKgh+gFp9d61ej+bkccgWAgQIECAAIHJCzwhJWRCsrL35EtRwVQLtO2K3IP0yXVt29a2pm1fOdX9UfxyCjyklJUX5qrMXJp52ytK2e+qROvNpax4Uw66+3Ie2L4JECBAoHcC9edG/V32br3rmQ5NTEBAmhh9/w68um33S0j6vxqQ8rglj3USBwuB2QIJRzUMvTg/zK5Ia0ft43nc/+pSdjtx9sqeEyBAgACBXQgISLsA8vb8BQSk+ZvZYicCGTm6Q4LRJTUkpV16eNv+1E5W99awBHJZXR05quFoJhjNfvx6Xr9R5v0ovz4sFr0lQIAAgUUI9CoguQdpEf8SbEqgqwL5ENn/2VLKI+pvwKlxnxWlnH5o2+7f1XrVNVaB+2b0aN9SnrWDg94xrz8w/25WPGoHK3iZAAECBAj0WkBA6vXp1bkhCyQk/W36/4fVIJM2rF1ZykczYJC5GywDF7hl/jnkvqOdTXJ4RP6drLr9wJ10nwABAgQGKiAgDfTE6/YwBDY0zSsyFPBntbcJSfdaW0q9Ad8ybIGLSjl/F9/7v59/Npuv+/DhYVPpPQECBAgQIDApAfcgTUp+CMdt21W5D+lfR/cj1YkbnjuEbuvjDgUylXedoKFOyDD73qOZ55fl9TqjXXnyDvfgDQIECBAgcEOBXt2DdMOu+WpSAgLSpOQHctxM2nCLBKNzRiHp2jy/90C6rpvbFahTedfZ6uqEDDPBqD7WcHT/XH636sxstrNr8La7Vy8SIECAwGAFBKTBnvrl67iAtHy29jwSyEx2d0lAuqqGpASkCxKa1sEZrEB+kNWpvOtsdccmEL0kwei4zOuxf0aOrgtHtxusjI4TIECAwEIEBKSFqNlmpwIC0k55vLlUAglFj5p1qd1/Hdi2+yzVvu1nKgUylfeK95Wy15cTjD6WHjwlzcjRVJ5KRRMgQGCiAgLSRPn7eXABqZ/ntZO9Skh63qyQdGqusMr8DRYCBAgQIECAwIIFehWQdjGT0YKRbEiAQEcFNpbyspRWpwCvM9sdlevszGzX0XOlLAIECBAgQGD8AgLS+M0dkcBkBZqmvfT6D5H9n1Ehx+WepIdPtihHJ0CAAAECBAh0Q0BA6sZ5UAWBsQpc0DSXZp7nI3Nnfj4T57rlXavb9mfHWoSDESBAgAABAgQ6KCAgdfCkKInAOATObJrvZNqyhyQkbc6ldnvkm8GpGUm6+TiO7RgECBAgQIAAga4KCEhdPTPqIjAGgTOa5pMJSE+vh0pIygeIllMyacOqMRzaIQgQIECAAAECnRQQkDp5WhRFYHwCG5vmzTnaa+oRE5LuuraUt9fnFgIECBAgQIDAEAUEpCGedX0msJXA+lL+MC99tr6ckPRbmQr8xVut4ksCBAgQIECAwCAEBKRBnGadJLALgaa59upSHpTL7TbWNROSnp/7kfIhohYCBAgQIECAwLAEBKRhnW+9JbBDgXOa5oJN+VykhKTLE5BulPahfKDs7Xa4gTcIECBAgAABAj0UEJB6eFJ1icBCBc5qmq8nID1mtP2N83h6RpJuutD92Y4AAQIECBAgMG0CAtK0nTH1ElhmgUzacHJC0jNGh7lNRpI+nJntVizzYe2eAAECBAgQINAJAQGpE6dBEQS6JbChaV6fik4cVfWra0ez3HWrStUQIECAAAECBJZeQEBaelN7JNALgUza8NsZSfqP2pmMIj0tl9rNjCr1on86QYAAAQIECBDYnoCAtD0VrxEgUDJpwxXXZNKGUJxXORKSXp7pv++OhgABAgQIECDQZwEBqc9nV98ILFIgIenMzZn+O7u5Nm33fMM4+ZC2PXyRu7U5AQIECBAgQKCzAgJSZ0+Nwgh0Q+CMpvmXLaU8cVTNQbuXclpC0l7dqE4VBAgQIECAAIGlFRCQltbT3gj0UiAz270z9yO9uHYul9odsaqU9/SyozpFgAABAgQIDF5AQBr8PwEABOYmsOH6gPSJ0doPzofIvnpuW1qLAAECBAgQIDA9AgLS9JwrlRKYrEDTbM4o0kNTxLdHhRyfSRseONmiHJ0AAQIECBAgsLQCAtLSetobgV4L5PORfpgOHpl2Se1oLrd732Fte6f63EKAAAECBAgQ6IOAgNSHs6gPBMYosL5pvpWRpIelbUlA2nu36ydtOGCMJTgUAQIECBAgQGDZBASkZaO1YwL9FchI0scTjp5Te5jHNZm04aTStiv722M9I0CAAAECBIYiICAN5UzrJ4ElFshIUp2k4c2j3d5zTSlvWeJD2B0BAgQIECBAYOwCAtLYyR2QQH8E1pfyrFxq96Xao3wzeUImbXh+f3qnJwQIECBAgMAQBQSkIZ51fSawVAJNc3V2dUxC0tl1l7nc7o9Xt+19l2r39kOAAAECBAgQGLeAgDRucccj0DOB3I/0/S2lHJ2QdFUC0op8U/nI4W17q551U3cIECBAgACBgQgISAM50bpJYDkFzmiaf8/+H1ePkZC034pSTj+gbfddzmPaNwECBAgQIEBgOQQEpOVQtU8CAxTISNIHM4r03Nr1hKQ7JB19IDPb5amFAAECBAgQIDA9AgLS9JwrlRLovMCGUl6ZkHTaqNDfXFvKyzpftAIJECBAgAABArMEBKRZGJ4SILBIgaZpLy/lUQlJ36h7yvDRc9a27ZMWuVebEyBAgAABAgTGJiAgjY3agQgMQ+D8prksAenItB/UHickvS6TNtxlGL3XSwIECBAgQGDaBQSkaT+D6ifQQYGNTbM+ZT04bVPaqkzacGo+I+kWHSxVSQQIECBAgACBGwgISDfg8AUBAkslkEkb/jmjSE+t+8so0i3yzebUXG63x1Lt334IECBAgAABAsshICAth6p9EiBwnUBC0p8lJL1yxHGXBKV3oCFAgAABAgQIdFlAQOry2VEbgR4IbCjl+QlJnx515VHr2valPeiWLhAgQIAAAQI9FRCQenpidYtAZwSaZtO1pRybkLSh1pTHP8z9SL/ZmfoUQoAAAQIECBCYJSAgzcLwlACB5RE4u2l+sDkz22Xvl+UyuybfeD6QkHSH5TmavRIgQIAAAQIEFi4gIC3czpYECMxD4Mym+a+MHj06Lf+VfROUTl/dtvvNYxdWJUCAAAECBAgsu4CAtOzEDkCAwIxAJm04NcHoafXrPN4q34BOLG2bWcAtBAgQIECAAIFuCAhI3TgPqiAwGIH1TfOmDCF9qHY4Iek+60p5/WA6r6MECBAgQIBA5wWGGJDqJT1r026Xdmja3mkWAgTGKJBPj31cQtJXRod8cu5HOn6Mh3coAgQIECBAgMDgBX4mAvXzV85Lq/c/bN2+k9f+PO3AtEksT8hBa03C2iT0HXMiAoe17aGZ8vv7aW3aNYe37T0nUoiDEiBAgAABAosV2D07qL/L3m2xO7L9eAT+KIeZCUQb8/zzaX+T9sG0j6V9Ke17aXWdC9IemTbuRUAat7jjdUJgbdv+QsLR1aOQdH4e13SiMEUQIECAAAEC8xEQkOajNeF1H5Lj1+BTg9Cdd1JLboUov5T25bS6/t3TxrkISOPUdqxOCSQk/fYoINWRpK8d3LZGUjt1hhRDgAABAgR2KSAg7ZKoOyv8dUqpl8+tmmNJ9f6kS9LeNsf1l2o1AWmpJO1nKgUSkk6YCUl5ftJUdkLRBAgQIEBguAK9Ckh9n6ThTvl3+oW0q+f47/WirPf1tDp5g4UAgZ0L7J+3a1v0sqGUl2To9uN1RxnOfWBC0usWvVM7IECAAAECBAgsQKDvAaneW/SzaSvnaFNHkGqo+uYc17cagaEJ1O8Zz8yg7Nl5rPfspV33PK+VhX8/aZotF5fy8ISkb2U/NSQ9PR8i++D63EKAAAECBAgQILB0Ao/Kruo9Rael3XUnu633INUZtOqEDZmBuPxi2jgXl9iNU9uxFiqQALR7JjjZJyOyr8r/r742avV5fW3307PjhYekbJyZ7W6T0aOL6uV2ebw87YiFFms7AgQIECBAYGwCvbrEbmxqEzpQDT7PSLs8rQals9K+mPa3aR8YPdZL8M5Jq+9fm/a0tHEvAtK4xR1vIQIZJapB6Fv5/0q7Vauv1ffq6NLiloSjX0sw2jy6J+mMTNpw0OL2aGsCBAgQIEBgmQUEpGUGXo7d3zI7rYGoXhZUg9DsVsPTt9NenXZ42iQWAWkS6o45T4F6KV0dLdo6HM18Xd+77nK7ee5329UTkJ4+a9KGf8kh6zdeCwECBAgQINBNgV4FpDrCMrTlxunwTdL2SKsfHJtbH5Z8uVn2+PK0uf5Sd5usW6cW3yetBjYLga4J1MkYcr/R1/JQb9Pb3vL1vPjT9Y0D0n5QnyxmSUh6Q75BPbXuI8nrXRua5vGL2Z9tCRAgQIAAgWUTqL/z1itJ6u+z9eqsqV4Wdb/AlPb8ktR9ZlodNVqOcDSlLMom0C2BDaU8O8Ho87WqBKXHZUTphd2qUDUECBAgQIAAAQLLJeASu+WStd8lFBjfJXYzRdf7jxKMzqiX22VEaVNmtvvVmfc8EiBAgAABAp0R6NUldp1RHXghAtLA/wFMSfczAcNOJ2m4Jv3IOku7rGnbn0k4umIUki6qM90t7RHsjQABAgQIEFikgIC0SECbbysgIG1r4pXuCazYyTTfCUeLn+Z7R11OOHpIDUijkPTN/dq23kdoIUCAAAECBLoh0KuA1PdJGmrwqJMyzHep9z2M8wazWufb00zSMN8zZf1xCyQk1anwVx2fezEPuf7gq87J89fk+evTtlz/2tL/b8LRs7PXV9Y9596kj28o5TdLPmC2fm0hQIAAAQIEJipQA1JvJmmYqOQYDv7VHCO/S827nTCG2mYfwgjSbA3Pp0WgzmxX23iWtm1yqd3JMyNJeaxT81sIECBAgACByQv0agRpt8l7LmsFv5G9n5R2t7RT096ZNpflW3NZyToEBi6w6Km85+XXNO2Vbfvova4f3b1jtj0+9yet39g0b5nXfqxMgAABAgQIEBi4wKr0/4tpddjvZzpqYQSpoydGWd0TyMjRmrTzRyNJV2VU6Re6V6WKCBAgQIDAoAR6NYI0hM9BqsHod0b/RN80qH+qOkughwLrm2ZjunVs2rVp9Q8gJ2dmu0PzaCFAgAABAgQILFpgCAGpIn0j7XlpdcKGemmOhQCBKRZISPpMyn9y7UJmmrn5ylxCm5C05xR3SekECBAgQIAAAQKzBFxiNwvDUwJzFcjldS8bXWpXP0j2A3PdznoECBAgQIDAkgq4xG5JOe2MAAECCxTYUMoLMk3lP9XNM5L08BqYFrgrmxEgQIAAAQIErhMYyiV2TjcBAn0UaJrNm0p5SELSd0fde05GlI7qY1f1iQABAgQIEBiPgIA0HmdHIUBgmQTOapoL82mxR2b3l2YUKf+Vv17dtj+5TIezWwIECBAgQKDnAgJSz0+w7hEYgsAZTfPfm0t5ZEaS8l/ZJ9/YTj+0bcf3IbZDQNZHAgQIECAwEAEBaSAnWjcJ9F0gIelvko6eUvuZYaR1mdnuxNK2ff8w7L6fVv0jQIAAAQJjFxCQxk7ugAQILJfAxqZ5S0LS++v+E5LuvbYUn322XNj2S4AAAQIEeiogIPX0xOoWgQEL1A+G/rfa/4SkJ2Zmuz8YsIWuEyBAgAABAvMUEJDmCWZ1AgS6LbChaa7KzHZHZyTpe7XShKSXJiTdu9tVq44AAQIECBDoioCA1JUzoQ4CBJZM4MymOSch6Zjs8Oq0eh/SiWvadt2SHcCOCBAgQIAAgd4KCEi9PbU6RmDYApn++18zs93vVoWMIu2fb3anHdi2+wxbRe8JECBAgACBXQkISLsS8j4BAlMrkJnt/irFv3DUgZ/aO5+RlJntkpcsBAgQIECAAIHtCwhI23fxKgECPRFYX8qf5n6kv6vdSTI6am0pr+9J13SDAAECBAgQWAYBAWkZUO2SAIEOCTTNlktKeURC0v/UqhKSnppJGx7WoQqVQoAAAQIECHRIQEDq0MlQCgECyyNwYdNckvuRjkxIumh0hHetbtufXZ6j2SsBAgQIECAwzQIC0jSfPbUTIDBngcxs950tpTwkIWlzRpH2zDe/UzOSdPM578CKBAgQIECAwCAEBKRBnGadJECgCmTShk8mHD2jPs/joXk4OZM2rKpfWwgQIECAAAECVUBA8u+AAIFBCaxvmjdlFOl1tdMJSb+wtpS3DwpAZwkQIECAAIGdCghIO+XxJgECfRTYUMpz0q/P1b4lJP1WLrV7UX1uIUCAAAECBAgISP4NECAwPIGmufbKUh6Ujp8x6vwLE5J+fXgQekyAAAECBAhsLSAgbS3iawIEBiHw/aY5Px09KpfbXZFRpBulfXBd295uEJ3XSQIECBAgQGCHAgLSDmm8QYBA3wVyP9LXEpAeM+rnTfJ4ekaSbtr3fusfAQIECBAgsGMBAWnHNt4hQGAAAhub5qRM/338qKu3yeOHMrPdigF0XRcJECBAgACB7QgISNtB8RIBAsMSSEh6bXr80drrXGr3a2tLeXV9biFAgAABAgSGJyAgDe+c6zEBAtsRuDqz2eVyu/+obyUkPT2X2j11O6t5iQABAgQIEOi5gIDU8xOsewQIzE3gnKa54ppSjs7a59UtEpJetaZt7z63ra1FgAABAgQI9EVAQOrLmdQPAgQWLZCQdMbm66f/vjY72z3fIE8+pG0PX/SO7YAAAQIECBCYGgEBaWpOlUIJEBiHwBlN8y+ZtOGJo2MdtHsppyUk7TWOYzsGAQIECBAgMHkBAWny50AFBAh0TCCTNrwzJb20lpVL7Y5YVcq763MLAQIECBAg0H8BAan/51gPCRBYgMD6Uk7IZv842vQhuR/plQvYjU0IECBAgACBKRMQkKbshCmXAIExCTTN5sxq95Ac7f/qETOS9KyEpAeO6egOQ4AAAQIECExIQECaELzDEiDQfYENTfPDhKQjU+klCUhN2vsOa9s7db9yFRIgQIAAAQILFRCQFipnOwIEBiGQkPTNTNrw8ASlLQlIe+92/aQNBwyi8zpJgAABAgQGKCAgDfCk6zIBAvMTyKQNH0s4ek7dKo9rMmnDSaVtV85vL9YmQIAAAQIEpkFAQJqGs6RGAgQmLrC+aV6dUaQ/GxVyzzWlvGXiRSmAAAECBAgQWHIBAWnJSe2QAIG+Cmwo5RkJSV+q/cs3zyesbdvn9rWv+kWAAAECBIYqICAN9czrNwEC8xdomquz0TEJSWePNv6TzGx3n/nvyBYECBAgQIBAVwUEpK6eGXURINBJgUza8P1M2nB0QtJVuR9pRdpHDm/bW3WyWEURIECAAAEC8xYQkOZNZgMCBIYucEbT/HsMHl8dEpButiIz2x3QtvsO3UX/CRAgQIBAHwQEpD6cRX0gQGDsAhlJ+kBGkp5fD5yQ9BNJR+/PzHZ5aiFAgAABAgSmWUBAmuazp3YCBCYqsLGUl6WA00dFPGBdKW+aaEEOToAAAQIECCxaQEBaNKEdECAwWIGmaS8r5ZG5H+kbI4PjMmnDIwfroeMECBAgQKAHAgJSD06iLhAgMDmB85vmslxqd1RC0oW1ilxj95eZtOEuk6vIkQkQIECAAIHFCAhIi9GzLQECBCKQSRu+m4D04DzdlIC0RyZtOCUjSbeAQ4AAAQIECEyfgIA0fedMxQQIdFBgY9N8KiNJT6ulJSQdkm+up2TShlUdLFVJBAgQIECAwE4EBKSd4HiLAAEC8xFISHpr1n/NaJufz6QNfzmf7a1LgAABAgQITF5AQJr8OVABAQI9ElhfynNzud2nR116VC61e3GPuqcrBAgQIECg9wICUu9PsQ4SIDBWgabZdG0pxyYkbajHzeV2z09I+s2x1uBgBAgQIECAwIIFBKQF09mQAAEC2xc4u2l+sLmUI/PuZQlIN8o32g8kJN1h+2t7lQABAgQIEOiSgIDUpbOhFgIEeiNwZtP8V0aRHp2W/8q+CUqnr27b/XrTQR0hQIAAAQI9FRCQenpidYsAgckLbGiaU1PFM2slCUi3yvTfH8nMdnmwECBAgAABAl0VEJC6embURYBALwQSkl6fIaQPjzpz33WlvL4XHdMJAgQIECDQUwEBqacnVrcIEOiOwKZSHpuQ9JVRRU9e27ZP7051KiFAgAABAgRmCwhIszU8J0CAwDIInNU0V2Zmu6Oz63Pr7nO53SsPb9t7LsOh7JIAAQIECBBYpICAtEhAmxMgQGAuApnZ7qwtpTww616TtnK3Uj66rm3XzGVb6xAgQIAAAQLjExCQxmftSAQIDFxgY9N8IZfa/d6I4cA8nnZw2+49cBbdJ0CAAAECnRIQkDp1OhRDgEDfBTJpw3sykvSSUT/vtGcp783MdrnqzkKAAAECBAh0QUBA6sJZUAMBAoMS2FjKizKS9Pe100lGD1pXyqsGBaCzBAgQIECgwwICUodPjtIIEOipQNNsubiUh6V3/zvq4fH5ENkH97S3ukWAAAECBKZKQECaqtOlWAIE+iJwUdNcnNkajkx/kpVKyTfj92T67yP60j/9IECAAAEC0yogIE3rmVM3AQJTL5CZ7eoI0kNzud2WXGq3V1qdtOGgqe+YDhAgQIAAgSkWEJCm+OQpnQCB6RdY3zT/kF48a9STw/cq5aRM2rD79PdMDwgQIECAwHQKCEjTed5UTYBAjwQys93r0p03j7r0i2tL+bMedU9XCBAgQIDAVAkISFN1uhRLgEBfBdaXcnwutftC7V8utXv8mrZ9fl/7ql8ECBAgQKDLAgJSl8+O2ggQGI5A01xzRSkPTIfPqp1OSPrjzGz3q8MB0FMCBAgQINANAQGpG+dBFQQIECjnNc25+RDZozKSdGUC0op8g/7wYW17GzQECBAgQIDA+AQEpPFZOxIBAgR2KbCxab6acPTYumIeb7pbZra7WdveeJcbWoEAAQIECBBYEgEBaUkY7YQAAQJLJ5CZ7T6cUaTn1j0mJN0+6eiDmdnO9+ulI7YnAgQIECCwQwE/cHdI4w0CBAhMTmBDKa9MSDqlVpCQ9BtrSnnF5KpxZAIECBAgMBwBAWk451pPCRCYJoGmaa8s5dEp+T9r2flm/ay1bfukaeqCWgkQIECAwDQKCEjTeNbUTIDAIATObZrLM4p0VDp7Qe1wRpJel5B010F0XicJECBAgMCEBASkCcE7LAECBOYikA+R3ZD1jk27Nm1V2imZ2e7QPFoIECBAgACBZRAQkJYB1S4JECCwlAKZtOEz2d+T6z4zinTzlaWcmpGkPZbyGPZFgAABAgQIXC8gIPmXQIAAgSkQSEh6ey63e+Wo1J/N47umoGwlEiBAgACBqRMQkKbulCmYAIGhCmwo5fkJSZ+q/c9I0sPXte1Lh2qh3wQIECBAYLkEBKTlkrVfAgQILLVA02zaVMqDE5K+W3edxz9MSKqTOFgIECBAgACBJRIQkJYI0m4IECAwDoGzmubCLaUcmWNdmlGk/Ff+enXb/uQ4ju0YBAgQIEBgCAIC0hDOsj4SINArgTOa5r83l/LIjCDlv7JPvpGffmjb7t+rTuoMAQIECBCYkICANCF4hyVAgMBiBBKS/ibDR0+r+8jjusxsd2Jp290Ws0/bEiBAgAABAtd9ODsGAgQIEJhGgcxs96YMIX2g1p6QdO+1pbxxGvuhZgIECBAg0CUBI0hdOhtqIUCAwPwFHp9N/q1ulpD0pDVte/z8d2ELAgQIECBAYEZAQJqR8EiAAIEpFNjQNFdlZrujM5L0vVp+vqm/PB8ie68p7IqSCRAgQIBAJwQEpE6cBkUQIEBg4QJnNs05CUnHZA9Xp9X7kD6akaR1C9+jLQkQIECAwHAFBKThnns9J0CgRwKZ/vtfM7Pd79Yu5VK7/fPN/bQD23afHnVRVwgQIECAwFgEBKSxMDsIAQIEll8gM9v9VS61e9HoSD+1dyl/lZntkpcsBAgQIECAwFwFBKS5SlmPAAECUyCwoZSXJCT9XS01yejotaW8tj63ECBAgAABAnMTEJDm5mQtAgQITIdA02y5pJRHJCR9sxackPT0TNrwsOkoXpUECBAgQGDyAgLS5M+BCggQILCkAhc2zSWZtOHIhKSLRjt+VyZtuPOSHsTOCBAgQIBATwUEpJ6eWN0iQGDYApm04f+2lPLQhKTNGUXaM9/sTz2obQ8etoreEyBAgACBXQsISLs2sgYBAgSmUiCTNvxjCn/mqPjD9irllEzasPtUdkbRBAgQIEBgTAIC0pigHYYAAQKTEMgHyb4xo0hvrMfOSNIvrC3l7ZOowzEJECBAgMC0CAhI03Km1EmAAIEFCmwo5VnZ9HN184Sk317Xti+szy0ECBAgQIDAtgIC0rYmXiFAgEC/BJrm2itLeVA6dUbtWEaUXpSZ7X69X53UGwIECBAgsDQCAtLSONoLAQIEOi3w/aY5PwUelXB0RUaRbpT2wYwk3a7TRSuOAAECBAhMQEBAmgC6QxIgQGASAuub5msJSL81OvZN8nhaRpJuOolaHJMAAQIECHRVQEDq6plRFwECBJZBYGPTfDS7/YPRrm+bxw9lZrsVy3AouyRAgAABAlMpICBN5WlTNAECBBYukJGkV2XrGpTqpA2/traUV9fnFgIECBAgQCDXoUMgQIAAgeEJXJ1L7XK53ddqzxOSnr6mbY8bnoIeEyBAgACBbQUEpG1NvEKAAIHeC5zTNFdck0kb0tE6eUP9a9lrE5Lu3vuO6yABAgQIENiFgIC0CyBvEyAwWIFD0/PHpD017QFpe6b1aklIOmPz9dN/X5uO7Z4fCCcd0raH96qTOkOAAAECBAjMW2D3bPHTaXvPe8ul2+AJ2VWudploDUvXG3siMN0C+Z6w4k258CzZYb+rSrntFckOCRArL0y3HjLdXdt+9Rk5+p1M+d3WllntvpKQtNf21/QqAQIECBDYrkD9fbr+Lnu37b7rxU4KPCxVvTntOWm3HlW4Tx4/lHZJWj2h+WWovDetTn077kVAGre44xHYocBuJ5ayf27R+Xi+L7SjdkUeX5xWQ1M/Q1KC0ctmQlIeP7xDHm8QIECAAIFtBQSkbU06+0q9hPDUtPxi86N2UZ6vTvuL0WufzOOfp/3r6OvP5jH3LI91EZDGyu1gBHYo8Ou5G2dTKV8fBaOZgDTzWEPSdSNJvbvcrk71nWD0iZmQVAPTDpW8QYAAAQIEbiggIN3Qo9Nf/X6qq+HoE2lHpv2/tO+mfTttS9qD02YvL8gXdf1HzH5xDM8FpDEgOwSBXQuseF8px+ZyuplAtPVjHUmql9tdd0/Srnc3ZWusbtv9EpC+XUNSAtKWXHr3wCnrgnIJECBAYDICAtJk3Bd01L/LVj9I22PW1nXWphqC/nbWazNP64jTGWlvmXlhgY+3zHZ1pOryObbc53BdTZO8DyolWAgMXWCvL5fyknx/2DoYzf663pN03cQNvcRKMLp9AtLFo5B02WFte8dedlSnCBAgQGApBXoVkHZbSpkO7mtNavqntBpAZpZ6SV0dPfrvmRdmPdbX16etnvXaQp5uyEYPTVs5x43vl/XqTFkWAgQmKrD5glK+X/+AspPLbM+vf0ipfwDp5bKhab6ZkaNHBOD0tL3zQ+K0TNpwl8x4FxsLAQIECBAgMO0CH0sH6sxTs0eQ6mV19Reg7Y0g1cB4aVpmsBrr4hK7sXI7GIEdCjwlEzTkDyqX5XvE7FGjmed14obrJmo4dId76MkbCUnH1VGk0UjSp8Mx1z/49ERANwgQIEBgHgK9GkGaR7+nctUnpuoahuooUr2W/g/Tzkr7alodLXpk2sxS/yr8rrS6/rEzL47pUUAaE7TDENiFQCZfWHVmKffPfUZbh6Q6cUOd3a5OAT6MJSHpvbNCUp3MxkKAAAECBLYnICBtT6Wjr9XQc0paDT0z7bw8Pzjt7aPXvpTHj6adPfr6H/I47kVAGre44xHYscDtrg9JdSTpuPwhpd6TVCduqLPb1SnAS/0hMIylbVflnqQvzoSkPD57GB3XSwIECBCYp4CANE+wLqxeR49elfaktJlLY26a5+9OOz+thqd64/Ub0yYxfa+AFHgLgQ4J1O8DudxuVS7TrRM31NntSqYAH96SUaRbJCSdPQpJ1+br+wxPQY8JECBAYBcCAtIugKbt7TrKtC5txQQLF5AmiO/QBAjsXODwtv25hKQra0jK4w8yHfgtd76FdwkQIEBgYAK9Ckg1HAx9qfcirU/bPHQI/SdAgMD2BM5smn/L64+v72Vmu5vlB8fpB7Ttvttb12sECBAgQGDaBQSkaT+D6idAgMAYBDL99wdymD+qh0pI+omko/eXts1TCwECBAgQ6JeAgNSv86k3BAgQWDaBDLX/SXZ++ugAD1hbyuuX7WB2TIAAAQIEJiQgIE0I3mEJECAwdQJN015ayqMyq803au0ZPnpqJm2Y/XEJU9clBRMgQIAAga0FBKStRXxNgAABAjsUuKBpLs2Nm0clJNUP4a4h6S8zicNddriBNwgQIECAwJQJCEhTdsKUS4AAgUkLnNE0301AenDq2JSAtEemAD2lTgc+6bocnwABAgQILIWAgLQUivZBgACBgQlsbJpPZSTpabXbCUmH5IfJKZm0YdXAGHSXAAECBHooICD18KTqEgECBMYhkJD01owkvW50rJ9fV8o7xnFcxyBAgAABAsspICAtp659EyBAoOcCG0p5TkLSZ0bdfHQ+SPZFPe+y7hEgQIBAzwUEpJ6fYN0jQIDAsgo0zbXXlHJsQtKG0XFemPuR7r+sx7RzAgQIECCwjAIC0jLi2jUBAgSGIHBO01ywKTPbpa+X5X6kG+UHywcSku4whL7rIwECBAj0T0BA6t851SMCBAiMXeCspvnPjCI9Ji3/lRvnh8tpq9t2v7EX4oAECBAgQGCRAgLSIgFtToAAAQLXC2xomlOSjp418rh1pv/+SGa2y4OFAAECBAhMj4CAND3nSqUECBDovEBmtnttQtKHR4Xed82PZ7nrfO0KJECAAAECVUBA8u+AAAECBJZUIPcjPTYh6St1p/kh85TMbPfUJT2AnREgQIAAgWUUEJCWEdeuCRAgMESB3I905bWlHJ2+n1v7n4kbXp37ke4xRAt9JkCAAIHpExCQpu+cqZgAAQKdFzi7ac7aUsoDU2hmAS8rcyPSSYe07erOF65AAgQIEBi8gIA0+H8CAAgQILA8Arkf6Qu51O73R3s/cPfMbHdw2+69PEezVwIECBAgsDQCAtLSONoLAQIECGxHIDPbvTsvv7S+lUvtfnrPUt6bme3y1EKAAAECBLopICB187yoigABAr0RWF/KCRlJ+vvaoSSjB60p5RW96ZyOECBAgEDvBASk3p1SHSJAgEDHBJpm88WlPCxV/W+tLD94nr2mbY/tWJXKIUCAAAEC1wkISP4hECBAgMCyC1zUNBdntoYjc6BkpetGkt6b6b+PWPYDOwABAgQIEJingIA0TzCrEyBAgMDCBDKz3f/mUruHpW3JpXZ7pZ2aSRsOWtjebEWAAAECBJZHYLcF7Pbe2eb+abdPu1na9pZ35sXaLAQIECBA4EcCmbTh73N53bMTjl6TF1fvlem/M2nDfUrT1OnALQQIECBAYOoEHpyK8/l/JX8AvK7lYy7K9toJed0yd4EnZNVqavrbuZtZkwCBKRbI5XVvXde27ai9Y4q7onQCBAgQKCWf5HDd77J3GyLGV9LpK9P+X9qaIQIsU58FpGWCtVsCBDoq0La7JyR9fiYk5flzO1qpsggQIEBg1wKDDUi5EqJsSvvQro2sMU8BAWmeYFYnQGD6BQ5q24MTkM6sISkBadPqtv2V6e+VHhAgQGCQAr0KSPOZpOGqnO46evTNQZ52nSZAgACBJRU4r2nOzTXaR+f64itzT9KK/ED68GFte+slPYidESBAgACBeQrMJyDVe43+Ka1O07qQyR3mWZrVCRAgQKDvAhub5isJR4+t/czjfvnhcvrN2vbGfe+3/hEgQIBAdwV2FZBuktL3n9Wen+dr0/4m7X5p69Jmvz/zfM+8biFAgAABArsUWN80H85f4OrPlxqSbp909MHStrv6+bTL/VqBAAECBAgsh8B/ZKd1drX5thOWo5ge79M9SD0+ubpGgMAcBNq2yX1IJ89M2pDHN89hK6sQIECAQDcEenUP0q4ulauX1H13Ae7uU1oAmk0IECAwWIGmaS9v28fsU8rnY3DHtOMSkr6U0aX3DdZExwkQIEBgKgRumSrrZXQ7WuolEfdKO2JHK3h9uwJGkLbL4kUCBIYmkFGktQlG549Gkq7K13cdmoH+EiBAYAoFejWCNN9rvP8xJ+zJOzlpq/LeP6f93k7W8RYBAgQIENiuwIam2ZBrumc+lLz+TDklM9sdut2VvUiAAAECBJZBYFeX2N0mx/ylWcfdN8/vnPY7s16beVrD1szI0YUzL3okQIAAAQLzEUhI+nRGjp6SCRvelnbzlQlJ+fqeeb1+3ISFAAECBAhMVKBOtXpOWv6gN+d2Wdb92TTL3AVcYjd3K2sSIDAQgVxm9+rRpXb1g2TfP5Bu6yYBAgSmUWD3FF3zwt2msfita97VCNIl2eABaT8x2vC1efxs2smjr2c/ZJbWckXaV9LOmP2G5wQIECBAYL4C60t57tpctZBRpF9Oe8Satv2/fG7SH813P9YnQIAAAQLLKfNydm8AAEAASURBVPD67PxBy3mAge7bCNJAT7xuEyCwc4Hcf3SzjB59p44k5XHL6ratH1ZuIUCAAIFuCfRqBGm+tOvmu4H15yQgIM2JyUoECAxRIKHoJxOQLhldbndJ/XqIDvpMgACBDgv0KiDNdxa7T+bEfDvtVWm/mDbf7bOJhQABAgQIzF3gjKb5xuZSHpWL2+v17fvmB89pdWRp7nuwJgECBAgQmLvAfAPOO7LrOovQs9I+l/a9tL9I+820Oh2rhQABAgQILLlAQtLp2ekz645zP9ItcwPtiaVtd3Uf7ZLXYYcECBAgQGBHAmvzxnFpH0urgan+Ve/StI+kPSrtJmmWuQu4xG7uVtYkQGDAAnU2u5mZ7fL4lgFT6DoBAgS6JNCrS+yWAnbv7OTotA+n1Znsalh6UZpl7gIC0tytrEmAwIAFEpD2SDD68kxIytdPHzCHrhMgQKArAr0KSPO9xG72SdgjX9w37Xlpz02rs9vlyoeSS8XLBWkWAgQIECCwpAL1w2KvLeWY/CWuXuJdf+i8MiHpXkt6EDsjQIAAAQLzELhr1n1h2qfSZi6tqyNG30x7c9oxaS6vC8I8FyNI8wSzOgECwxZIKLprRpGuGo0knZ+v1w5bRO8JECAwUYFejSDNV/K72aAGoovT/jLtt9MOS7MsTkBAWpyfrQkQGKBAwtFjZi61y+PXD2zbfQbIMLvLe+WLm6etmP2i5wQIEBiDQK8C0nwvsft6gOsldDdOqzPX/dqorcmjhQABAgQIjE1gfdO8Lze+vmR0wDvmhtj3lbatl3oPbblXKXt8MZ2ukyXl0sMVeVz57jy/RZqFAAECBMYgUC+hq5fSvTXt22l1RKm2+vxtaQ9O2y/NMncBI0hzt7ImAQIEfizQtjfK5XV/O2sk6dU/fnMQzx6bO7Hyh8vHbirlM/lZ/M20E9PudHVC0nkRuOUgFHSSAIFJC/RqBGkpMNdlJ/UX/A+kzdyX9KI8t8xdQECau5U1CRAgcAOBm7XtjROS/mdWSHroDVbo7xe3yue1Z86KtyYQtVu1q/P1fa/JyNK/9bf7ekaAQIcEehWQ5nuJ3dbn4aC8cPe0e6TdO61+WGyd6tssdkGwECBAgMDyC1zYNJdk+OTIJIKL6tHy+O41bXvn5T/yxI/wxIwUZfToSdsppP6u8o6V+btldbjLdlbwEgECBAgskUD9jnvvtJel/XtaDUP5WVQuTzs57XFpB6ZZ5idgBGl+XtYmQIDANgKr2/ZXMpK0aTSSdOZBbXvwNiv16oU9P1fKC/IzeOvRo9lfr7kiXU6QshAgQGBZBXo1grTbPKm+lvVvP9rm+3l8R9ppaf+YVi+vsxAgQIAAgYkInNE0/5iA9Mwc/A1ph2VKt5OTHe5dmiaXmlkIECBAgMDyCPxNdvvStPp5SEOcKWh5VK+/h6uOxGUSJgsBAgQILEYgI0hvmrkfKYHpXYvZV8e3fVUpR+SPk7NHjGY/X19/rtQrPVxi1/ETqTwCPRDo1QjSYs7Hmmx8v7RHpP1K2s3SLAsTcIndwtxsRYAAgW0F2nb3BKTPzYSk3I/0vG1X6sUrJmnoxWnUCQK9EBh8QPqJnMZPp9W/TM1u9RKGelmDkaUgzHMRkOYJZnUCBAjsTODgtj0oAWljDUkZRdqcVv+g18flsab57uNp1ScCUycw6IB0eE7XxWk1GH0s7U/T/iDtTWnfSauv/2XaYmfHyy4GtQhIgzrdOkuAwDgEEoqOSLt8NJL0w0Pb9rbjOO4EjnGv0QfFbs6x83N4RSZmWPnuPPdBsUGwECAwFoFBB6STQpwPnyv33Q71yrz25rQakuq035a5CwhIc7eyJgECBOYskMvrjk1I2jIKSd/K85vOeePpWzHzUpSbp62YvtJVTIDAlAsMOiD9ICfvjTs5gXVWvPrJ3S/YyTre2lZAQNrWxCsECBBYEoGEoueOAlK93O7jpW0FiCWRtRMCBAj8SKBXAWk+l8LdJAR1Iob/+hHFtk825aVvpd1527e8QoAAAQIExi+woZRX5KgfrUfOTbL3W3v9ZeH1SwsBAgQIENhGYD4Bqd57VNsR2+zlxy/U9HiHtPU/fskzAgQIECAwQYGmaXNTzm/n+u+v1SoSkp6UkaTHTrAihyZAgACBDgvMJyDVbnw8rV4O9oD6xVbLHvn6z9L2T/vUVu/5kgABAgQITEzg3Ka5PFOtHpUCzq9FJCT9ee5PutvECnJgAgQIEOiNwJr05KK0/CGufDat3o/0x2nvTDszrb7+kTTL/ATcgzQ/L2sTIEBgQQKr2/YeuR/pmtE9Sd/PzHaHLWhHNiJAgACB2QK9ugdpdsfm+vzQrFin+K5haHa7PF+/MK2OJFnmJyAgzc/L2gQIEFiwQEaOfnfWpA1fOaxt91zwzmxIgAABAlWgVwGpzjo3n+UtWfnKtCPTahC6fdrBaevT6ucg1SnALQQIECBAoLMCG5vmHbkH6Ta5zO4P0n4mPwjfnWIf1tmCFUaAAAECnRVYlcouS/tmZyuc3sKMIE3vuVM5AQLTKJCpvjOK9ImZkaQ8vnQau6FmAgQIdESgVyNI85mkIfe3lkvT6gfR5Y9uFgIECBAgMKUCTbN5cykPTfX/V3uQ68X/MKNKx0xpb5RNgAABAksoMJ+AVO83euDo2Kfl8X5pt0q78XZaHW2yECBAgACBzgqc0TQXbbl+ZrtL8le/Ju19uR/pjp0tWGEECBAg0EmBz6WqC9JmT86wvecv6mT13S3KJXbdPTcqI0Cg5wKZtOH+GT3aXC+3y+P6Q9r2gJ53WfcIECCw1AK9usRuvpM01PuP6jTfu1q+tasVvE+AAAECBLogkEkb/i7h6Omp5Y0ZRVqbn/IfLW37KxlTurYL9amBAAECBAgMUcAI0hDPuj4TINApgYSk99VRpNFI0ts6VZxiCBAg0G2BXo0gzecepG6fFtURIECAAIFFCKwv5Xez+b/WXWQk6fdz6d3xi9idTQkQIEBgSgUEpCk9ccomQIAAgSUWaJqrM2nDMbmx9py65/yAfHlC0i8v8VHsjgABAgQ6LjDfe5BOTn8O2UWf6ofFXpz23bSPpNWJHSwECBAgQKDzArkf6XuHZ7rvFaV8JqNIe6SduLpt75IZ7+rPNAsBAgQIENhG4B/yyiVpMzPX1SB0dlo+TuJHr828Vx83pT0izbJzAfcg7dzHuwQIEBirQEaOHjnrfqT/OqBt9x1rAQ5GgACB6RLo1T1I86X/uWxwRdr70tbM2nhlnj867fy0V6XtmXaPtP9Mq+Hp9mmWHQsISDu28Q4BAgQmIpApv0+YCUl5PC0z22VAyUKAAAEC2xEYdECqN6/WUaQd/ZA4Ku/VkaM7pdXlsLT6dQ0Alh0LCEg7tvEOAQIEJiPQtjdKMDp9JiQlML1uMoU4KgECBDov0KuANJ9JGuqo0M+knZJWQ8/2lo/nxdzjet3oUX3/rLRvp92tfmEhQIAAAQJTI9A0Wy4t5ZH5gfffteb8ZfDpCUkuG5+aE6hQAgQILExgPgHpqhyifkhsHRXa0XJo3qj7vHzWCvW67flOBjFrc08JECBAgMBkBC5omkvzV78jE5IuHFXwzkziUC83txAgQIBATwXmE5DqqNHfpz017S7b8dg7r7159PqXRo+/nMebp31z9LUHAgQIECAwVQJ1Brv8AHxIit6UUaQ9MsPdqZnE4RZT1QnFEiBAgMCyCRyRPdfPh6gTL5ye9rK0E9LekXZeWg1Rf5JWl3oZQl2vTupQQ5JlxwLuQdqxjXcIECDQCYGEouNm3Y/0xUzasKoThSmCAAECkxfo1T1IC+GsfzX7RNq1aTUQzbQanI5Lm5nA4eV5/uW0u6dZdi4gIO3cx7sECBDohEDuQXrDTEhKYHpvJ4pSBAECBCYvMPiANHMK6l/O6qV2dea6n0qrMJaFCQhIC3OzFQECBMYr0LYrE5I+PROS8vjC8RbgaAQIEOikgIDUydMy3UUJSNN9/lRPgMCABA5p2wMSktbXkJTHzRlJuv+Auq+rBAgQ2J5ArwLSfCZp2B6G1wgQIECAwKAEzmmaCzbl6olcX355rim/UX6QfiAh6Q6DQtBZAgQI9FhAQOrxydU1AgQIEFgegbOa5j+z50cnJNX7cG+cH6anrW7b/ZbnaPZKgAABAuMUEJDGqe1YBAgQINAbgQ1Nc0pGkJ4z6tCtM/33h0vb5sFCgAABAtMsICBN89lTOwECBAhMVGB907wqQ0gfHhXxK2tLee1EC3JwAgQIEFi0gIC0aEI7IECAAIEhC1xTyuMSkr5aDTKi9NTcj1Q/8sJCgAABAlMqICBN6YlTNgECBAh0QyCTNlyRkHR0qjm3VpQfrK/L/Uj36EZ1qiBAgACB+QoISPMVsz4BAgQIENhKICHpzC2lPCgvJyuVlbkR6aRMB756q9V8SYAAAQJTICAgTcFJUiIBAgQIdF9gY9N8PpfaPXFU6YH5UJDTEpL26n7lKiRAgACB2QIC0mwNzwkQIECAwCIEMrPduxKSXl53kfuRfnpVKe/NzHZ5aiFAgACBaREQkKblTKmTAAECBKZCYEMpL0hI+odRsceuLeVPp6JwRRIgQIDAdQICkn8IBAgQIEBgKQWaZnN297C0/x3t9jmZ2e7YpTyEfREgQIDA8gkISMtna88ECBAgMFCBXGr3w3T9qLSLc31dk/bedW370wPl0G0CBAhMlYCANFWnS7EECBAgMC0C+RDZb+VSu4enbUlAqpM1nHbztj1wWupXJwECBIYqICAN9czrNwECBAgsu0BGkj6egPTU0YFW75npvzNpQya4sxAgQIBAVwUEpK6eGXURIECAQC8EMv33WxKS3jPqzD3WlfLWXnRMJwgQINBTAQGppydWtwgQIECgOwIbSvn9hKQvjCr6ndyP9OzuVKcSAgQIEJgtICDN1vCcAAECBAgsh0DTXH1FKQ/Mrs+qu09Yetnqtv2V5TiUfRIgQIDA4gQEpMX52ZoAAQIECMxJ4LymOXdLKUcnHF2ZSRtW5Afwhw9r21vPaWMrESBAgMDYBASksVE7EAECBAgMXSD3I30lBo+rDglJ++2Wme1u1rY3HrqL/hMgQKBLAgJSl86GWggQIECg9wKZ2e5D6eQf1Y4mJN0h6egDmdnOz+Pen3kdJEBgWgSG/g15RU5UvbzhptNywtRJgAABAvMSuFXWfmUpe37u+lafl/raRJf1pfxJLrU7tRaRkHT/taW8bqIFOTgBAgQIDErgoPT2bWnvmtXrm+T5n6VdlZafUWVz2tfTjk+bxPKEHLTWsfckDu6YBAgQ6KnAY0u50bWlHJHv9S/I99ja6vP6Wsl7k10ObNt9Mpvdf6a1o/aYyVbk6AQIEFiwQP18t/q77N0WvAcbjk3ggBzprLR6wj49OurKPP776LUajD6V9pG0jaPXanAa98iagBR0CwECBJZQ4F4Zm8n3+Lfm+3+7Vauv1fdK1pnssibZKOHo/FFAumpt2951shU5OgECBBYkICAtiG0yG702h80PwvLctFWjEp4xeu3tebz56LX6UE/sG9Lq+r+aNs5FQBqntmMRIDAAgT2+mEGiTduGo5mwVN+r60x+SSi6VwLSNTUk5fk5mdnu0MlXpQICBAjMS6BXASmXPvd6qR/Kd3Bavc8os6tet5yU//3ltHrpXb3MYvZSR442pH0g7TlpC13qfu6bVker5rLcLys9NW2ftMvnsoF1CBAgQGCHAnvlnUtL+Uy+F99zByt9Nq//Uv25sG9aPqJoskuC0RPzA7lewVCXf8tf6u6ZyRxyOaCFAAECUyFQA9LVaXdPq79/T/Wy21RXv+via/++mjYTjuoW9bKKM9K2Dkf1vbreOWm3qV8sYlmbbT+cVv+xzGVZMZeVrEOAAAECcxLIxHD1Uun6d7AdLde9V/+YVdedeEBKGHpbQtJtE5LqVQ4/l/bOtEemWQgQIECAwJIKvC17uyRt/1l7fUqeX5l24KzXZp7WS+5y2UU5YeaFMT26xG5M0A5DgMAgBPJHpxUJPSdmIGbmkrqtHz+S9+o6pTt/oGrb3RKS/ml0P1K93G7cP4sG8Y9DJwkQWBaBXl1ityxCHdpp/StcHe47M23mOot66cXn0j6VdkjazHJEnvxvWr2k4Y4zL47pUUAaE7TDECAwFIGV7y7lTvn+f/V2QlJ9rb5X1+nWcmjb7p9g9J3R/UibV7ftkd2qUDUECBDYroCAtF2W7r74uJRWR4zq5XNfS6uXLfzF6Otr8vjfaeem5QfmdevUsDLuRUAat7jjESDQd4FbJACdl9tB831+/ayQVJ/X1+p7Jet0b0ko+skEpEtGI0mX1K+7V6WKCBAgcAMBAekGHNPxxcEp82Vp9d6jegldDUOz22X5uk7M8FNpk1gEpEmoOyYBAn0XuGVmqvu3dDJ/IFuTy+lqq8+vey3vdXdJODoqI0lbakiqI0qZ2e5m3a1WZQQIELjuvvv6u/XdWEynQL3evE6h+vNpNRDdNG3Si4A06TPg+AQI9FngLuncE0etPp+KJZ+RdPxoFKmGpH8quUdpKgpXJAECQxQwgjTEs77MfRaQlhnY7gkQIDCNAglG758JSXl88zT2Qc0ECAxCoFcBqU5xaiFAgAABAgQ6KJBrwn8nZdXLBOtyXAJT/cw8CwECBAgso4CAtIy4dk2AAAECBBYjcFbTXJkP7TsmF/Z/v+4nn5P06owk/dJi9mlbAgQIENi5gIC0cx/vEiBAgACBiQokJJ2dAo5Jy9TkZWXaRzOStDaPFgIECBBYBgEBaRlQ7ZIAAQIECCylwIam+VL293ujfR6QkaTTDmzbfZbyGPZFgAABAtcLCEj+JRAgQIAAgSkQWN80702ZLx2Vese9S3lfZrZLVrIQIECAwFIKCEhLqWlfBAgQIEBgGQXWl/JHuR/pY/UQSUbHrCnlFct4OLsmQIDAIAUEpEGedp0mQIAAgakUaJotF5fyiISkb9b680P82Zm04aFT2RdFEyBAoKMCAlJHT4yyCBAgQIDA9gQuapqLM/33UQlJF9X38/jufKjsnbe3rtcIECBAYP4CAtL8zWxBgAABAgQmKpCZ7b69pZSHJRxtzqV2e+aH+SkHte3BEy3KwQkQINATAQGpJydSNwgQIEBgWAJnNM0n0uPjR70+fK9STs6kDfXT7C0ECBAgsAgBAWkReDYlQIAAAQKTFMj032/IKNKf1RoyknS3taX8+STrcWwCBAj0QUBA6sNZ1AcCBAgQGKzAhlKens7/SwVISHpsPkT2ufW5hQABAgQWJiAgLczNVgQIECBAoBsCTXPNFaU8KMWcMSroTxKS7teN4lRBgACB6RMQkKbvnKmYAAECBAjcQODcpjkvl9odnXZFRpFW5M0PHtq2t73BSr4gQIAAgTkJCEhzYrISAQIECBDotkDuR/qPzGz32wlJbULSTVeWctp+bXuTbletOgIECHRPQEDq3jlREQECBAgQWJBAZrY7MQHpBXXjhKTbJR19KDPb1RElCwECBAjMUUBAmiOU1QgQIECAwDQIbCzlZQlJJ9VaE5Lut66UN0xD3WokQIBAVwQEpK6cCXUQIECAAIGlEGia9spSfish6Wuj3R2XSRseuxS7tg8CBAgMQUBAGsJZ1kcCBAgQGJRAJm24PKNHR6fT59eO5/nb1rTt3QaFoLMECBBYoICAtEA4mxEgQIAAgS4LrG+ajZtKOTY1Xpu2Kj/wT87Mdod1uWa1ESBAoAsCAlIXzoIaCBAgQIDAMgic2TSfzcx2/2+064Mzs92ph7XtnstwKLskQIBAbwQEpN6cSh0hQIAAAQLbCmxsmnfk1dfUd3Kp3Z13K+Vd267lFQIECBCYERCQZiQ8EiBAgACBngqsL+U56dona/cSkh6W+5Fe3NOu6hYBAgQWLSAgLZrQDggQIECAQMcFmmbz5lIekir/r1aakPSCzGx3TMerVh4BAgQmIiAgTYTdQQkQIECAwHgF8iGyF+V+pKNy1EsSkJq09+V+pDuOtwpHI0CAQPcFBKTunyMVEiBAgACBJRHI/Uj/k5D0yHxGUh7KPrkf6bRD2vaAJdm5nRAgQKAnAgJST06kbhAgQIAAgbkIJCT9bdY7vq6bUaS1u5dyYmnbTHBnIUCAAIEqICD5d0CAAAECBAYmsKFpXp8u/1XtdkLSvdaW8qb63EKAAAECApJ/AwQIECBAYJACuczuCen4v9bOJyT9fiZtePogIXSaAAECWwkYQdoKxJcECBAgQGAIAhlFuio3Ih2ToHRO7W9C0qsy/fcvD6Hv+kiAAIGdCQhIO9PxHgECBAgQ6LFA7kf6Xqb/riHpqnRzt4Skj6xu21v2uMu6RoAAgV0KCEi7JLICAQIECBDor8CZTfPlBKTfrT1MQNo/vxicdkDb7tvfHusZAQIEdi4gIO3cx7sECBAgQKD3AhlJ+utcbveS2tGEpJ9MOvrrzGyXpxYCBAgMT0BAGt4512MCBAgQILCNwMZSXpQX/2b0xpHrck/SNit5gQABAgMQEJAGcJJ1kQABAgQI7FKgabZcev2HyP73aN3jM7PdI3a5nRUIECDQMwEBqWcnVHcIECBAgMBCBS5omkszacNRuSfpwtE+3nl42/7cQvdnOwIECEyjgIA0jWdNzQQIECBAYJkEMmnDdxKQHpLdb8pNSHusKOWUTP99i2U6nN0SIECgcwICUudOiYIIECBAgMBkBTJpwz9l0oZn1CoSkg5NOzmTNqyabFWOToAAgfEICEjjcXYUAgQIECAwVQIJSW9OwW+pRScg3XVNKX8xVR1QLAECBBYoICAtEM5mBAgQIECg7wLrM4qUy+0+U/uZXxgek0vtntf3PusfAQIEBCT/BggQIECAAIHtCzTNtdeUcmxC0oa6QkaSXpKQdP/tr+xVAgQI9ENAQOrHedQLAgQIECCwLALnNM0Fm0o5OiHp8gSkG+UXhw9k+u/bL8vB7JQAAQIdEBCQOnASlECAAAECBLoscFbTfD0B6TFp+a/cOEHptNVtu1+Xa1YbAQIEFiogIC1UznYECBAgQGBAApm04eR0d+YepNtk+u8PZWa7PFgIECDQLwEBqV/nU28IECBAgMCyCWxompdn5x8ZHeBX15bypmU7mB0TIEBgQgIC0oTgHZYAAQIECEyjwNWlPDbX2X211p5L7Z6USRt+Zxr7oWYCBAjsSEBA2pGM1wkQIECAAIFtBDJpwxWZ2e7ovHFufTO/SLw19yPdY5sVvUCAAIEpFRCQpvTEKZsAAQIECExKICHpzC2lPCjHT1Yqu+dGpI8e0rarJ1WP4xIgQGApBQSkpdS0LwIECBAgMBCBTNrw+Vxq98RRdw/avZRTE5L2Gkj3dZMAgR4LCEg9Prm6RoAAAQIEllMgkza8KyHplfUYuR/piFWlvCcz2+WphQABAtMrICBN77lTOQECBAgQmLjAhkz9nZD0D6NCHryulJdMvCgFECBAYBECAtIi8GxKgAABAgQGL9A0m2PwsLT/rRYJS8/LzHbH1ucWAgQITKOAgDSNZ03NBAgQIECgQwK51O6HKeeotItzfV2T9p51bfvTHSpRKQQIEJizgIA0ZyorEiBAgAABAjsSWN8038ro0cPTtiQg7Z3HU2/etgfuaH2vEyBAoKsCAlJXz4y6CBAgQIDAlAlkJOnjKfkZteyEpDV7lnJSJm1YOWXdUC4BAgMXEJAG/g9A9wkQIECAwFIKJCS9MaNH7xnt8x7r8kGyS7l/+yJAgMByCwhIyy1s/wQIECBAYGACG0r5/YSkL466/buZtOH4gRHoLgECUywgIE3xyVM6AQIECBDopEDTXJ26Hph2Vq0vl9u9YnXb/kp9biFAgEDXBQSkrp8h9REgQIAAgSkUyKV238/838dkJOnKBKQV+YXjw4e17a2nsCtKJkBgYAIC0sBOuO4SIECAAIFxCZzRNP+eYz2+Hi8hab/dSjntZm1743Ed33EIECCwEAEBaSFqtiFAgAABAgTmJJCRpA9mFOlFdeWEpDvcpJT3Z2Y7v3/MSc9KBAhMQsA3qEmoOyYBAgQIEBiQwIZSXpyQdOqoy7+5tpTXDKj7ukqAwJQJCEhTdsKUS4AAAQIEpk6gadrLS3l06v6vWntGkp6eSRvq1xYCBAh0TkBA6twpURABAgQIEOifwPlNc9mWUo7KSNIPau/yC8hfZNKGn+9fT/WIAIFpFxCQpv0Mqp8AAQIECEyJwMamWZ9SH5y2KaNIe2TShlMOb9tDpqR8ZRIgMBABAWkgJ1o3CRAgQIBAFwQyacM/ZxTpKbWWhKRb1JC0tm336EJtaiBAgEAVEJD8OyBAgAABAgTGKpCQ9LaEpDeODnqXPP7lWAtwMAIECOxEQEDaCY63CBAgQIAAgeUR2FDK8QlJ/1z3npGkR65r2xfW5xYCBAhMWkBAmvQZcHwCBAgQIDBEgabZdG3uR0pIWl+7n8cXZWa7BwyRQp8JEOiWgIDUrfOhGgIECBAgMBiBs5vmB5szs106fFlGkW60Ih8im5D0E4MB0FECBDopICB18rQoigABAgQIDEPgzKapn430qIwg5b+yb34xOS3Tf99sGL3XSwIEuiggIHXxrKiJAAECBAgMSGB905yWEaTn1C7n8VaZ2e4jpW3zYCFAgMD4BQSk8Zs7IgECBAgQILCVQELSqzKE9MH6ckLSfdaV8vqtVvElAQIExiIgII2F2UEIECBAgACBXQlsKuXxWeffR+sdt6Ztj9vVNt4nQIDAUgsISEstan8ECBAgQIDAggTOaporM7Pd0RlJ+n7dQX5JeV2m//6lBe3MRgQIEFiggIC0QDibESBAgAABAksvkJB0dvb6wLSr01amfXRt267No4UAAQJjERCQxsLsIAQIECBAgMBcBTY0zRez7u+N1j8g9ySdenDb7j3X7a1HgACBxQgISIvRsy0BAgQIECCwLAKZtOG9udTu5aOd32nPUt6Xme2SlSwECBBYXgEBaXl97Z0AAQIECBBYoMCGUp6fkPSxunmS0QPXlvKn9bmFAAECyykgIC2nrn0TIECAAAECCxdomi0Xl/KIhKRv1p0kJD03kzY8ZOE7tCUBAgR2LSAg7drIGgQIECBAgMCEBC5qmosz/fdRCUk/rCXk8d2Z/vtnJlSOwxIgMAABAWkAJ1kXCRAgQIDANAtkZrtvbynloQlHmzOKtFd+eTn1oLY9eJr7pHYCBLorICB199yojAABAgQIEBgJnNE0n0hAetroy8P3KuWkTNqwOyACBAgstYCAtNSi9keAAAECBAgsi8DGpnlLQtI7684zknT3taW8bVkOZKcECAxaQEAa9OnXeQIECBAgMF0CG0p5Uir+l1p1QtLjMmnDs+tzCwECBJZKQEBaKkn7IUCAAAECBJZfoGmuuaKUB+VAZ9aDZUTpZQlJv7b8B3YEAgSGIiAgDeVM6ycBAgQIEOiJwLlNc16CUZ3Z7oqMIq3I44cObdvb9qR7ukGAwIQFBKQJnwCHJ0CAAAECBOYvsKFp/iPh6LEJR20eb7qylNP2a9ubzH9PtiBAgMANBQSkG3r4igABAgQIEJgSgfVN85GEoxNquXm8XdLRBzOz3YopKV+ZBAh0VEBA6uiJURYBAgQIECCwa4H1pfxJRpFOqmsmJP362lJeu+utrEGAAIEdCwhIO7bxDgECBAgQINB1gaZpryzlt1Lm12upCUlPXdu2v931stVHgEB3BQSk7p4blREgQIAAAQJzEMikDZdntaPSzq+rJyT9+Zq2vVt9biFAgMB8BQSk+YpZnwABAgQIEOicQO5H2riplGNT2LVpqxKSTsrMdod1rlAFESDQeQEBqfOnSIEECBAgQIDAXATObJrPZr3j6roJSDfPzHanHta2e85lW+sQIEBgRkBAmpHwSIAAAQIECEy9QEaS/iKTNry+diQh6c67lfKuqe+UDhAgMFYBAWms3A5GgAABAgQILLfAhlKenWN8sh4nIelhmbThhPrcQoAAgbkICEhzUbIOAQIECBAgMD0CTbMpNyI9NCNJ3xkVfUJC0tHT0wGVEiAwSQEBaZL6jk2AAAECBAgsi8BZTXPhlutntrsko0hN2l8d3rb/v707gZejqtM+fio3C0kggbBlQlYii8jEBWFARmFEfFF5w64gCoiiMCjDDMIw6DtREEURVBDxZYQXQUC2ABkdGB0WcUAUUTYFB15zs4AQIBjIvtU8z73V0NPpvvd2p253Lb/z4U9XV1VXnfM9uX3736fq3F0H5WQcFAEECiVAglSo7qQxCCCAAAIIIFARmB9Fv1eS9GGNJOkhbNoVwpwJcbxVZTuPCCCAQD0BEqR6KqxDAAEEEEAAgUIIzIuiHytBOsON0SjStOEh3BTiWBPcURBAAIH6AiRI9V1YiwACCCCAAAIFEVCSdIGaco2boyRpn6khXORlCgIIIFBPgASpngrrEEAAAQQQQKBQAhpF+oQa9KAbpSTpRE3acEqhGkhjEEAgNQESpNQoORACCCCAAAIIZFWgO4pWrg3hYCVKz7qOSpIumBLHf5PV+lIvBBDonAAJUghbi39nBRad+3fImRFAAAEEEBh0gQVR9Oy63iRppU42VEnSjZPjePtBPzEnQACBXAmQFITwWfXYE4rNc9VzVBYBBBBAAAEEmhZQkvRgcrmdR5G21AehOVvF8WZNH4gXIIBAYQWGFrZlvQ2boYfR/bRxu2T77np8JVleoMeFyTIPCCCAAAIIIFAgAU3acM20OH6jmvQ5JUlv2lR/I+nFOD5Yfy1JuRMFAQQQKLbAw2qe3+yajVltZjkhqWN/yVybq8XpEEAAAQQQKKhAHA9RkvQjRezQpA1fLWhLaRYC7RDQDPo9n7f3asfJBvscRR9B+q4Av6HYRDFH4Uvpaotv0NxD4Sk/VyQb70seW30Ypxeep/A/loGUHQayE/sggAACCCCAQEoCUbR+SRx/eEwIv9Ao0i6KM5QkPazJHK5L6QwcBgEEcipQhgTp5+qbaxX7K/5D8W1F9RC6vzFygvRFxWIFBQEEEEAAAQRKILA4il4ZHcczu0L4lRIkf7l5+aQ4fkr3Kf26BM2niQggUHKBEWr/1xXrFT9RVO470mJwguSEyW+MnSpcYtcpec6LAAIIIFB6Ac1kt58us1uTXGq3UCNJ40uPAgACzQkU6hK7ssxit0p97Nnq3qPwTZmPKY5UUBBAAAEEEECg5ALzo+hOfYP692bQSJK/RL0lxLG/XKUggEAJBcqSIFW69i4teGa7nyp8jbEvvdtCQUEAAQQQQACBEgtoZrtv63KSS02gJGnPqSFcVmIOmo4AAiUV+KjavUThy+u4xK6k/whoNgIIIIAAAq8JxPEwXWZ3ry+1Sy63O/O1bSwggEBfAlxi15dOjrZdrbq+WXGT4h7FGgUFAQQQQAABBMoqEEVrNJ3tYfrWdF5CcO6UOH5fWTloNwIIINBJASZp6KQ+50YAAQQQQKBKYGIcz9BEDUuTkaQ/a3nnqs0sIoDAhgKMIG1owhoEEEAAAQQQQKAYAguj6FGNIh2j8CX4Y3VP0hzNdMc9y8XoXlqBQL8CZZukoV8QdkAAAQQQQAABBDRpw2xlR59PJHbQ30q6XjPb6YGCAAJFFyBBKnoP0z4EEEAAAQQQaElANyJ9RS+8MXnx/tNC+FZLB+JFCCCQKwESpFx1F5VFAAEEEEAAgbYJRFGsP6R4nEaSHk7OebImbTi+befnRAgg0BEBEqSOsHNSBBBAAAEEEMiDwLNRtHx1CDNV10Wurz44Xar7kfbOQ92pIwIItCZAgtSaG69CAAEEEEAAgZIIKElasC6EQ9Vc5UphuG5Emj0hjieXpPk0E4HSCZAgla7LaTACCCCAAAIINCswP4ruWx/CScnrttGcxrcpSRrV7HHYHwEEsi9AgpT9PqKGCCCAAAIIIJABAc1sd4WqcYGroqm/3zIihO9rZjstUhBAoEgCJEhF6k3aggACCCCAAAKDKjA3hH/UCX6anOTwKSF8cVBPyMERQKDtAiRIbSfnhAgggAACCCCQW4EoWqdZ7T6o+j/lNmj46POa2c73J1EQQKAgAiRIBelImoEAAggggAAC7RHojqI/K0nyzHZLlCBFiqumxfGb23N2zoIAAoMtQII02MIcHwEEEEAAAQQKJ6Ak6UlN2nCUEqX1SpBG6/G28XG8deEaSoMQKKEACVIJO50mI4AAAggggMDGC2jShtt1lNN8JCVJU0aGcLMmbRi28UfmCAgg0EkBEqRO6nNuBBBAAAEEEMi1gEaSvqnRo6uSRrxzSgiX5LpBVB4BBPwHoSkIIIAAAggggAACrQp0h/BJJUkP+PX6YHXC1Dg+tdVj8ToEEOi8AAlS5/uAGiCAAAIIIIBAngWiaJWqf4iSpGfcDF1ud/7kON4vz02i7giUWYAEqcy9T9sRQAABBBBAIBUBXWr3nCZtOEhJ0godcKg+YN0wMY7fkMrBOQgCCLRVgASprdycDAEEEEAAAQSKKjA/ih5S2453+zSKNG5oCHPGxfGYoraXdiFQVAESpKL2LO1CAAEEEEAAgbYLaCTphxpJOscnVpL0xrEhXKuZ7fi81fae4IQItC7AD2zrdrwSAQQQQAABBBDYQGBeCLN0qd2cZMMHpoXwtQ12YgUCCGRWgAQps11DxRBAAAEEEEAglwJRFC8L4WjV/fGk/qdp0oaP5LItVBqBEgqQIJWw02kyAggggAACCAyuwAtRtFSX2s3USNJLPpM+cP2LJm3YY3DPytERQCANARKkNBQ5BgIIIIAAAgggUCMwL4rmatXhirW6H2kTTdpwy6Q4nlCzG08RQCBjAiRIGesQqoMAAggggAACxRHQpA33aBTpFLdISdIEJUm36g/JblKcFtISBIonQIJUvD6lRQgggAACCCCQIQElSZeqOpckVdpdidL3MlQ9qoIAAjUCJEg1IDxFAAEEEEAAAQTSFtC1dqdqJOme5LhHT4njs9I+B8dDAIF0BEiQ0nHkKAgggAACCCCAQGOBKFq7RvcjKUlSrtRzud05mtnuwMYvYAsCCHRKgASpU/KcFwEEEEAAAQRKJfBMFL20TjPbqdFLdZndkC79EVklSbuUCoHGIpADARKkHHQSVUQAAQQQQACBYggsiKLHNYr0EYX+C5vpg9gcTf89rhitoxUIFEOABKkY/UgrEEAAAQQQQCAnApq04TZVteceJI0kTdfMdjeGONYDBQEEsiBAgpSFXqAOCCCAAAIIIFAqASVJ52kI6YdutJKkd08N4aJSAdBYBDIsQIKU4c6haggggAACCCBQXIG1IRyv1j3kFipJOmlaHH+yuK2lZQjkR4AEKT99RU0RQAABBBBAoEACC6NoxeoQDtZI0nNJs76tJOldBWoiTUEglwIkSLnsNiqNAAIIIIAAAkUQ0Mx2C9WOQxSrFMMUN02N46l6pCCAQIcESJA6BM9pEUAAAQQQQAABC+h+pAc0ivSpRGNrXW5327ZxPBodBBDojAAJUmfcOSsCCCCAAAIIIPCagJKk768P4fxkxYyRIVytme2UK1EQQKDdAiRI7RbnfAgggAACCCCAQB2BeSGcqZGkO7xJmdEh00I4p85urEIAgUEWIEEaZGAOjwACCCCAAAIIDEggitYvCeFIJUl/8P56PEuTNhwxoNeyEwIIpCZAgpQaJQdCAAEEEEAAAQQ2TuDlKFqyJoSZSo7+rFGkSI9XTonjt27cUXk1Agg0I0CC1IwW+yKAAAIIIIAAAoMsoJnt/kvJ0YeUHK3T4yh9WLttmzjedpBPy+ERQCARIEHinwICCCCAAAIIIJAxgblR9BNV6R+Sak0aFcJsTdowPGPVpDoIFFKABKmQ3UqjEEAAAQQQQCDvAprZ7iKNIv0/t0MjSe+YGsJ3894m6o9AHgRIkPLQS9QRAQQQQAABBEop0B3CiUqS7nfjlSR9TPcjnVZKCBqNQBsFSJDaiM2pEEAAAQQQQACBpgSiaPXyEA7Vaxb4dUqSvqqZ7d7b1DHYGQEEmhIgQWqKi50RQAABBBBAAIH2CiyKouf1R2QP0kjSciVIXXq8frs43rG9teBsCJRHgASpPH1NSxFAAAEEEEAg2wLTVb2vhTDyP3vDy8Hrwrwo+q2So+O8rMfNh4UwZ4s4HuvnOSsjVd/PhDDidk3Q96Dyvav1/ICctYHqIoBAGwRO0Dn0hVAY3YZzcQoEEEAAAQQQyJ7AcSEM0Z9AesvKED6vzwQOL3tdb2LkKk+N41m6xC52aPl2zWyXpy+7d1JitCCELdWukzUodo7aeJjaN2RtCENvUvOYpc+dnM/ivvNn2b3yWX1qnUUBEqQs9gp1QgABBBBAoD0C+2hcaF0I39EHzLgmvM7bgvZRieNIidHsqiTpwp712f+fRo6cHL1fCdHSmjY+qudbrtJo0sXZbwY1bCBAgtQAhtWtC5AgtW7HKxFAAAEEEMi5wCYPaJBIoyi1yVHlubd5n96ybRyPVoL0SFWSdGxlW4YfdVmdR45qk6NKG+9QktSTCG6X4TZQtcYCJEiNbdjSogAJUotwvAwBBBBAAIGcC+hvwAaNEN1bM6pSSRz86G3eJ3jfnqJRpKlKkBYlSdJKPd+zsi2bj77nyJfVVberdnkLJVDho9msP7XqR6BQCVKerlvtp1/YjAACCCCAAAII5E5gjGqsz2Pb9FHxnm3+zOZ9e4r+iGy3Fg5X+B6lEYpbNLPdRD1mtHRtFcJ4zS/RV9laCVTYoq892IZAOwRIkNqhzDkQQAABBBBAAIH6Ai/o3psVITxef2vP2sf0f+8TtO/rZW4U3atnn/YaZR7j9RX+rRPj2LPEZbCsejKEh3WpYKPi5nUP0//+2GgP1iOAQLkEuMSuXP1NaxFAAAEEEKgSGHZlCDM0ScGqOpfZeZ23eZ/6RZfXfavqfqTr6u/V8bWaytuz1XlChtpL6/z8bMWwxaplRhO8jvtlvQKFusQu69hlqR8JUll6mnYigAACCCCwocBfKDlYFMJ+q0OYW5VAeNnrvC1onwYljocqSbqzkiTp8f802LPDqz2Vt2er84QMlSRpuZadHPVM0HBEhyvI6VsXIEFq3Y5XNhAgQWoAw2oEEEAAAQRKIrC9Zqr7tdqq+3CmLO8NL/es07a+iy6tG6ck6WknSXpcrzio71d0ZKs+RHsqbydDnpBhR7VzuO6h6hk5IjnqSJekdtJCJUj93CyXGhoH6lvACdJlik0Vy/rela0IIIAAAgggUGCB3dW23ZL2PaTHBwfa1slxvEtXCJ4OfDPFUl3PtteCKOrr5qaBHjrt/TyV97sVnpDB9xzdqfBNSJT8CjhB0uhgeIfiF/ltBjXPkgAjSFnqDeqCAAIIIIBATgWUJB2o0aN1yUjSHzWz3ZY5bQrVzpdAoUaQhuTLntoigAACCCCAAAIINBKYH0U/0uVBZ3q7HqcNC+GmoHuUGu3PegQQ2FCABGlDE9YggAACCCCAAAK5FdD03+er8te4AUqS9p0awkVepiCAwMAESJAG5sReCCCAAAIIIIBAbgQ0LdwnVNme+5eUJJ00JY5Pzk3lqSgCHRYgQepwB3B6BBBAAAEEEEAgbYHuKFqpSRoOVqL0Jx9bH/i+qXuT9k37PBwPgSIKkCAVsVdpEwIIIIAAAgiUXkAz2D2bJEmaUjv4PqSbNJI0rfQwACDQjwAJUj9AbEYAAQQQQAABBPIqsDCKfqU/puTZcn0/0pb64Ddn6zj2nxWhIIBAAwESpAYwrEYAAQQQQAABBIogoJntfqBL7c5L2rLraE/gEMfKlygIIFBPgASpngrrEEAAAQQQQACBAgl0h/A5NefHbpIyo5lTQ/iylykIILChAAnShiasQQABBBBAAAEEiiUQReuXhPBhjSQ94YYpSTpTkzYcWaxG0hoE0hEgQUrHkaMggAACCCCAAAKZFlgcRa9o0oaZSpJeTip6xeQ43i3TlaZyCHRAgASpA+icEgEEEEAAAQQQ6ISAJm14WpM2HKFzr9Uo0siuEG7VSNL4TtSFcyKQVQESpKz2DPVCAAEEEEAAAQQGQUCTNtypJOnU5NAT9XiLJm0YMQin4pAI5FKABCmX3UalEUAAAQQQQACB1gXmRdElSpL+xUfQSNKeU0O4rPWj8UoEiiVAglSs/qQ1CCCAAAIIIIDAgATmhXCydvy5d1aSdMy0OD59QC9kJwQKLkCCVPAOpnkIIIAAAggggEBdgShasyKEwzRpg3KlEPy3kqbE8fvq7stKBEokQIJUos6mqQgggAACCCCAQLXAc1H0gkaPDlJytEyPQ/TB8DpN2rBz9T4sI1A2ARKksvU47UUAAQQQQAABBKoE5kbRI0qQjlHovzBWidIcJUmbV+3CIgKlEiBBKlV301gEEEAAAQQQQGBDAU3aMFuJ0axkyw56vF4z22kWcAoC5RMgQSpfn9NiBBBAAAEEEEBgA4G5IXxJK2/yBiVL750awoVepiBQNgESpLL1OO1FAAEEEEAAAQTqCURRvCqEY3Wd3cPerCTpFE3acHy9XVmHQJEFSJCK3Lu0DQEEEEAAAQQQaELg2ShavlqTNugli/wyfVC8dHIc793EIdgVgdwLkCDlvgtpAAIIIIAAAgggkJ6AkqT560I4VEdUrhSG60ak2RPieFJ6Z+BICGRbgAQp2/1D7RBAAAEEEEAAgbYLzI+i+9aH8LfJibcZHsJtSpJGtb0inBCBDgiQIHUAnVMigAACCCCAAAJZF9DMdpfrfqRvup66H+mtI0K4UjPbaZGCQLEFSJCK3b+0DgEEEEAAAQQQaFmgO4TP6sU/TQ5wxNQQ/jlZ5gGBwgqQIBW2a2kYAggggAACCCCwkQJRtE73I31IR3kqOdIszWzn+5MoCBRWgASpsF1LwxBAAAEEEEAAgY0X0P1IL+tSu5k60hJdXxcprpoYxzM2/sgcAYFsCpAgZbNfqBUCCCCAAAIIIJAZge4oelKTNhylRGm9EqTRQ0OYMz6Ot85MBakIAikKkCCliMmhEEAAAQQQQACBogpo0obblSCd4fYpSZoyMoSbNWnDsKK2l3aVV4AEqbx9T8sRQAABBBBAAIGmBJQkXaAk6arkRe+cEsIlTR2AnRHIgQAJUg46iSoigAACCCCAAAJZEegO4ZNKkn7p+uiD5AnT4vgzWakb9UAgDQESpDQUOQYCCCCAAAIIIFAWgShapaYerCTpmaTJF06O4/3K0nzaWXwBEqTi9zEtRAABBBBAAAEEUhXQpA3PafpvJ0krdOCh+kB5w6Q4np7qSTgYAh0SIEHqEDynRQABBBBAAAEE8iywIIp+rfp/3G3QpA3jujSz3bg4HpPnNlF3BCxAgsS/AwQQQAABBBBAAIGWBDSSdJ1e+GW/WEnSLmNDuEYz2/H5siVNXpQVAf4BZ6UnqAcCCCCAAAIIIJBDgbkhfF6X2s1Jqn7g1BC+ksNmUGUEXhMgQXqNggUEEEAAAQQQQACBpgWiKF4awkeUJP3Or9VI0hlT4vjopo/DCxDIiAAJUkY6gmoggAACCCCAAAJ5FXgxil5dH8JMJUkvuQ1Kkr6nSRt2z2t7qHe5BUiQyt3/tB4BBBBAAAEEEEhFYH4U/VEJ0hE62FolSJto0oZblSRNSOXgHASBNgqQILURm1MhgAACCCCAAAJFFpgXRXdrJOnv3EYlSROGhnDL1DjepMhtpm3FEyBBKl6f0iIEEEAAAQQQQKBjAkqSvqORpEuTCuzhy+06VhlOjEALAiRILaDxEgQQQAABBBBAAIHGAt0aRVKS9LNkj6M1inRm473ZgkC2BEiQstUf1AYBBBBAAAEEEMi/QBStWR3C4UqS5iaNOVcz230g/w2jBWUQIEEqQy/TRgQQQAABBBBAoM0Cz0bRi2tDOEinXarL7IboQ+e1k+N4lzZXg9Mh0LQACVLTZLwAAQQQQAABBBBAYCACC6PoMY0i+W8k6b8wRh8850yM43EDeS37INApARKkTslzXgQQQAABBBBoRmCkdj5QcYrio4rtFJQcCHRH0W3Kjj7vqmokafqwEG4IcawJ7igIIJAFgf4SQk3ZH7ZQtHs6yhN0Tn+zMlpBQQABBBBAAIH/KaC/rTNscQjD14Sw43L9ql6pj9rrQui6WLsN/5+78iyrApqo4YfT4jhOwn1HKY6Afw79WXav4jSp2C3ZVs27XqE31rBUcbdib0W98hatdOfOqrdxENeRIA0iLodGAAEEEMi1gJIjJ0Nn6/fzckWcxB163HJVCENvynXrSlR5XVo3UknSQ1VJkj//UIohQIKUo37cVHWdr9CbaFiieFKhv18W9EYbzlXUFhKkWhGeI4AAAggg0DkBXVbnkSMnR5XEqPrxUa0fonkAwgGdqyJnbkZguzieqCTpT0mStHpSHL+zmdezb2YFCpUg9XfJWWZ7YYAVO137TVJ8UTFRsbNid8XjirMUFyooCCCAAAIIIJBNgf00erRZCJ9tULu/1PpDlCR1Hd1gB1ZnTOCZKFqoDjtU1dLoXximG5FuVrI0JWPVpDoIFFrgp2rd84raGwHHat29Cv2MBidRlZLWCNL2OuDLimUDDF1L3VMX34BKQQABBBBAAIFegVN67zmqHjWqXT5Hv8tHPQhYvgQ0inRs1aV2j2wbx9yHna8urK1toUaQahOH2sbm/fl2asDPFR5+ry6+3M4z4XjbVxXzFDco0irdOtAHFcMGeMA3ar+vK3zpHwUBBBBAAAEEegX0ZeML/Vzt8pwSpHUvApYvAc1s930lSB4CPE0xQ98QX6WrKA8PUeQvrykIIDCIArfr2H9WNJqVzgnUfMUKxd6KtEaQdKimimf88BuCs28KAggggAACCPQK6Pe0J2jwhAy1I0d+vlThGe3CpwHLoUAcd2kk6fbKSNKUOD47h62gyr0ChRpBKnqn+qJlJx6+12hCg8bupPWLFB5V+pzC+89StLOQILVTm3MhgAACCORIwFN5e7Y6T8hQnSQ5OXr/mhBGLFBjuEQ9Rz1aXdUt4niskqQnnSTpcf1kjyJR8ihAgpSjXvPI0e8UTnp8+dqRinrFI0e+Z8j7Ob6gaGchQWqnNudCAAEEEMiTgD54eSpvz1Z3mBIi33N0smak3VIjRz3Jkb/opORYQDPb7ajk6OUkSVqmZX8uo+RLgAQpX/0VNlV9v6WYq/CsKY3KdG3wJXkkSI2EWI8AAggggEDnBDSVd9fVvRMyjPDv688oGDnqXH+kemYlR+9VYrQ2udxuniZt2CbVE3CwwRYgQRps4UE8fj83evac2dOA+6bBdhZGkNqpzbkQQAABBBBAIHMCSpBOTRKkWI//GeLYH7op+RAgQcpHP+WqliRIueouKosAAggggAACgyGgJOmKSpKk5csH4xwcc1AECpUgDWREZVAUOSgCCCCAAAIIIIAAAtUC3SGcqHsd7ve6KITjPapUvZ1lBNohQILUDmXOgQACCCCAAAIIINC/QBStXt57z7hnJ3T5uma22793kf8j0B4BEqT2OHMWBBBAAAEEEEAAgQEILIqi5zVN4UEaSVquUaQufVi9YWIc7zCAl7ILAqkIkCClwshBEEAAAQQQQAABBNISmBdFv1Vy9DEfT4+bDw1hjv9mUlrH5zgI9CVAgtSXDtsQQAABBBBAAAEEOiIwN4pu0EjSOT65kqSdlR1dp5nt+Ozakd4o10n5R1au/qa1CCCAAAIIIIBAbgTmhTBLl9rd4gorSXrftBC+lpvKU9HcCpAg5bbrqDgCCCCAAAIIIFBwgSiKl4VwjFr5aNLS0zQNuJ9TEBg0ARKkQaPlwAgggAACCCCAAAIbK/BCFC3VKNJBOs6LybEu0/Tfe27scXk9Ao0ESJAaybAeAQQQQAABBBBAIBMC3VHUrYocplijGKG4RTPbbadHCgKpC5AgpU7KARFAAAEEEEC1DsloAAAVe0lEQVQAAQTSFtCkDffqmJ/2cXU/0vhhIdymJGlk2ufheAiQIPFvAAEEEEAAAQQQQCAXAkqSLlNFL0kqu5um/74iFxWnkrkSIEHKVXdRWQQQQAABBBBAoNwCc0M4Vfck3WUFjSQdOSWOzyq3CK1PW4AEKW1RjocAAggggAACCCAweAJRtHZtCEcoSfr/PomSpC9pZruZg3dCjlw2ARKksvU47UUAAQQQQAABBHIusDCKFq8PwUnRq0qQ9F/4waQ43jXnzaL6GRHQpZuUDAkMV110zyEFAQQQQAABBBBAoC+B+VE0b+Lzz39s6Dbb3KAMabOuOJ4z7rrr9ll81FGL+3od2wZFwElqYQoJUja60lNWurza+8D/EUAAAQQQQAABBPoTWLjttmHkAQeEUYcc4l2nrf3DH+aHIbpAar3GlyidEFjdiZOmfc5CZXtp47T5eG/X+c5VbKq4UkHJt8DFqv7/VTye72aUvva+XONTis+UXiL/AMclTbgy/00pfQt4fy3GPwHeX4vRj27FcYqlCk+W8ZCCgkCqAlfqaA5K/gWWqQnvz38zSt8C96H7kpJ/gSvVBAcl/wK8v+a/D90C3l+L0Y9uxZVJeLkQhUkaCtGNNAIBBBBAAAEEEEAAAQTSECBBSkORYyCAAAIIIIAAAggggEAhBEiQCtGNNAIBBBBAAAEEEEAAAQTSECBBSkORYyCAAAIIIIAAAggggEAhBEiQCtGNNAIBBBBAAAEEEEAAAQTSECBBSkORYyCAAAIIIIAAAggggEAhBEiQCtGNNAIBBBBAAAEEEEAAAQTSECBBSkORYyCAAAIIIIAAAggggEAhBEiQCtGNNAIBBBBAAAEEEEAAAQTSEBiaxkE4RmoCq1M7EgfqtID7ck2nK8H5N1rAfcjP5UYzZuIA9GMmuiGVSvD+mgpjxw/C+2vHuyC1CvD+mholB6onME4rHZT8C2yvJjBCm/9+dB+6Lyn5F+D9Nf99WGkB768ViXw/8v6a7/6rrj3vr9UaLCOAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQDMCXc3szL5tE9heZ9pLsUtyxpfadmZOtLEC/ply3+2hWKtYrKDkU4Cfw3z2W1+1nqCN71EsUqzoa0e2ZVZgvGq2j8I/n68qliko+ROYrCr/tWJHxSrFEgUlHwJTVc0PKB7ro7p8FuoDh03NC/iN/1ZFXBN36bl/GVCyLbCDqveEorr/fqfnk7JdbWpXI8DPYQ1IQZ76F/b9Cv98+ksMSr4Exqi6sxXV769Ocv8pX80ofW1HSOB7ivWKSl96+TLFJgpKtgX8c/h7hb+caFT4LNRIhvUtCQzRq+5R+A3jesX7FPsoLlf4zeNxBW8eQshoiVSvexWvKD6ieIPiBMVyxTzFaAUl+wL8HGa/j1qt4T/rhZUPZCRIrSp27nW/Svrvy3r8S8VxCn8B5T49UkHJh8A3VE332b8p9lfsp/ixwusuUlCyK7CFqnaHwn3VKEHis1B2+y+3Ndsn+UfnbzhrS+XN44jaDTzPjMBJqonfND5VUyMnSfXW1+zG04wI8HOYkY5IuRq+5HWNwpfW+eeRBEkIOSq+nMf99t2aOvsydK+/p2Y9T7Mp4A/P/hLRH67HVlVxs2S9RwSHVq1nMTsCh6gqzyr887ZK0ShB4rOQcCjpChyrw81VfKLOYf3tmP9RzqqzjVXZEPilqrFSsXlNdTwc7Tf9B2vW8zSbAvwcZrNfNqZWHr19SvFzxfkKv5fuqaDkR+BuVfVlRb2rKN6t9bvnpymlrummar3vzf1NHQVfgeGfzW3qbGNVZwV8RZP75kXFTIX7r1GCxGch4VDaJ3CWTuV/nL50i5I9gWGqkr9RebRB1X6r9asV3o+SXwF+DvPZd763wd9aT1Ocp/B7KQmSEHJU3H9zkvp6FOJNihkKRhsSlBw9+IsK/wy6/ypluhbWKR6urOAxUwK+FPIcxbikVo0SJD4LZarbil+ZrdTEFxSe4WV88Zubyxb6Gy+/4d/doPZ3JtsnNNjO6uwL8HOY/T6qV8ODtNI/m8cnG0mQ6ille90YVc99+G2FL/Px70M/d3iG18MUlPwI+P6xxxTLFT9Q+D5rj0Y8rWAkUAg5KI0SJD4L5aDzilLF0WrIAwr/Ivh4URpVwHa8IemjGxu0zevdhzs02M7qbAvwc5jt/mlUO3+h9ILCM4NWCglSRSI/j29UVf3++YhipeIChROlzyqcIHnb/1JQ8iHgiXDcd+636viCnnsbJfsCjRIkPgtlv+8yW8PhqpnvUamNehX2N9aesMFvIN+qtwPrMiMwUTVxP93coEazk+3bN9jO6uwK8HOY3b7pr2b/ph2eV2xdtSMJUhVGThb/SvWsfJA+pqbO+yXbnqhZz9NsCvgzkD/X+JL0v1d4xMFxqsLJ7z0KfyFFybZAowSJz0LZ7rdM1+6jql3ljb76cZOaWvt6XN9U7H2+VLONp9kTGKoqeSr2uxtU7R6td19u2WA7q7MpwM9hNvtlILU6WTv5Z+5DilFV4dEHr983Wef7WSjZFpis6rnPPANhbfGIw58U3u4vHinZFvBIn/tqVp1qnp5s8+ggJdsCjRIkPgtlu98yXbu/Ue3+tU74W5VK2VULzyo8Je0JlZU8Zl7gOdXwkQa1fFTrlym6GmxndfYE+DnMXp80U6O7tLM/iPUXOzVzUPbtiIA/dPkG/scbnP1arXc/cwlzA6AMrb446as316mTJ1FxP15RZxursiXQKEFyLQvzWchvPJT2CdytUzkalbdrw78rPBPIBxQ/UVDyIeBLPP5a4UuyPBVmpfjyHl9D/wuFf8lTsi/Az2H2+6i/Gt6iHep9oN5b69+muFHhX+QvKyjZFlir6j2tcDLr0cDliuryF3rifvQ+lGwL+EoLF19WV1sqXxTzRWKtTL6e81koX/2Vi9qOVC3nKnwd7l65qDGVrBY4VE/87dcZ1Su1fGay/vCa9TzNpgA/h9nsl7RqdZ4O5J/TPdM6IMdpi8CJOov77Qs1Z5uh506gfGUGJfsCR6iK7sebFLUTMnw92caVM4LIeOlrBInPQhnvvDxW72xV2m8czyhubRCf0HpKNgX8Zv97hUeJzlG8R/Gl5PlsPVLyIcDPYT76qdVakiC1KtfZ143Q6f3+6t+RlygOUPiDtCfheE6xvYKSfQHf8+erZNyPcxS+R9B9+T2F192vYARJCBkvfSVIfBbKeOflsXq/VaX9BtFXMJtdtnvWl9fdrvBlBJV+9C+D8QpKPgT4OcxHP7VaSxKkVuU6/7rNVIVrFKsUfn/1fbr3KXzJJCU/Ap6l7nxFpR/dl6sVTnzHKijZF+grQXLt+SyU/T6khgh0RMC/yHdTkBh1hJ+TIoBAgQV8r8oMhd9nKfkVGKqq76zYRTEsv82g5n0I8FmoDxw2IYAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIDA6wJ7aPEQxfDXV7GEAAIIIIAAAggggAACCAyewDAd+nTFhwbvFC0f+Ua9MlZs3fIRsvfCdnu3+3zZE6dGCCCAwEYIDNmI1/JSBBBAAIF8CnxQ1f6aYtMMVv83qtOPFaszWLdWq9Ru73afr1UXXocAAghkUmBoJmtFpRBAAAEEyirwlbI2nHYjgAACCGRDoCsb1aAWCCCAAAJtEninznOg4u2KFxVbKOYqVilctlL8b8VhioMU0xXe9ryiUvwaX563QrFGMVNxnGKGYpmi1X310rCPYl/FHxRrFc2cS7v3WcZrq9t2vOItipcVLyhqy5u04miF27iTwu1/TlFd9tWT3RW/V7xNcZTiYIUvDXxKsU7h0p+399lBcYTC5/T57FptqKc9Jmmdz8ejIIAAAggggAACCCCAgASuUfgen0qs17I/lLs4IXLC4G1LFCuTZX/YP0NRKU6EvM/Zit8ly74kzuucMH1SUSnN7OvX1N6D1OzrK+etfTxBK1w/t/dPybLb5WSpulyoJ07MvN+zyaP38/rqqy5mJ9v/IdnH7fbxHb9RjFO49OXt7acpnID5fAsUPrfPd64iUlRKWuerHI9HBBBAAAEEEEAAAQQQSAQ8UuEP8h+vEhmj5VcULyk8utSlGK3wqIg/wC9XjFW4zFBUko0btLyXwsmDEyzvu1gxSuHSzL7ev1GC5ASiv3P59fWKR42ceNyp8CiSyy6KJxROCCvtcrLkdt2h2Fbh4hG1OQqvdzJTKbO14DotUpyo8EiXj/0jhff9J0Wl1PP2NtfL+/5MMUHhspniWoXXH6uolDTOVzkWjwgggAACCCCAAAIIIFAlUO8D+57a7sSgOmmqvORfteAP7LsmKypJT7ee107H7STG+3ofl2b29f6NEqRubevvXH59vXKfVjrBcwJTXXyp4X8pfCmdR2teVjhBrCRMWuwpThQ96vSqwssuTljczk/5SVVx4uX13l4p9by97UmF993NT6qKz+H6egSrMoqUxvmqTsEiAggggEAjgerLBRrtw3oEEEAAgeILPKAmHlDVzGFanq7wvTqV0ZRRVdu9+JCidra5bm9QGdP78Nr/m9n3tRdVLbT6+iE6xpsVv1DU3kfk0R6Hy1TF5oqrFb68sLos05NbFCcpdla4LpVyf2UheexOHmvbX7Nbz7l20sqnFGsUM2p2eFDP36XwyNIzVdtaPV/VIVhEAAEEEOhLgASpLx22IYAAAuUSeIOa68vI9lV42b8jfBmZR05cKqMZvc82TDi8fmWy0YlJdalNTryt0b7Vr6sst/p6J3kekVlQOVCDRycrLvN6Hzb4f2W9XaoTpNp6DbRNOyRn8OMjG5zt9RU+X3WC1Or5Xj8iSwgggAACfQr4lx8FAQQQQACBnUXg0YnNFP+u8EjKwwqPZHxB8beK2uLkaaClmX3rHbPV13t0xqV29Kt37ev/9yiRi5OpesUuLpUEqPdZbwJZWW7msXIcW5/fxwsfr9nWqkPNYXiKAAIIINBIgASpkQzrEUAAgXIJnKLmeqKB4xTfV1SXHZMnXdUrc7I8X/X0ZYDT69R3a627TuEk5apku+8hqlcq6ysjSfX2aWbd09rZ9x9tpfDkEbXlr7TCs9lVRu9qt/McAQQQQGCQBGovgRik03BYBBBAAIEMCVRGVapHS6Yl9ZtbU8+36vleybphNdvy8NQjLrcr3qbYu6bCHhXbT+EvC/13hx5QvFfxdkV18eQUMxW26etyuOrXVC/X816hHX6i8AQN76/eWctvUtyruFzhJKrZUu98zR6D/RFAAIHSCpAglbbraTgCCJRYYFHS9k/r8auKSYq7knXf0ONRinco/lHhD/GrFC6Vv+3T+yw//z9dVfUlbZ6Q4e8UByi+o/D6Pyq+q3Cxh6cD/w+F78Vy8uT9f6ZYojhE0UrCUs9bh+o5tut1s2KWYn/FGYrbFB6t+7iikuxoccCl0fkGfAB2RAABBBBAAAEEEECgTAIeMfmhwh++/YH/cIU/kF+qcILgdY7nFCcoPKLi55VEwjOu+fnFitpytlZ427uSDc3s65fcqPDrffmbS7Ov733Vhv/3qMwvFT52JZz8TVdUl7fqya8VlX083bYTJo9AVZfZeuJ9tqxeqWV/8ej1lYTTm+t5e73LzgqPFvlyuso5F2r5WEV1Set81cdkGQEEEEAAAQQQQAABBKoERmp5m6rnXhyj8NTeE/ykgKXSvv5Gw7zfDMXwFA3qeVcOP0oLdp+icLKaRunrfGkcn2MggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBALgT+G5QV8RNHaJbsAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(reg.data$tannin,reg.data$growth,pch=21,bg=\"blue\",asp=1,xlab=\"tannin content\",ylab=\"growth\")\n",
    "abline(lm(growth~tannin,data=reg.data),col=\"cyan\",lwd=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the line does not go through all the points.  But it does capture the gist of the relationship between the two variables."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Store the model**<br/>\n",
    "In R, \"<-\" and \"=\" mean the same thing.  The arrow is literally saying \"take this and store it in there.\"  In this case, take the prediction (model) and store it in the R variable named <i>fitted</i>."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fitted <- predict(lm(growth~tannin,data=reg.data))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Plot the error (residuals)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(reg.data$tannin,reg.data$growth,pch=21,bg=\"blue\",asp=1,xlab=\"tannin content\",ylab=\"growth\")\n",
    "abline(lm(growth~tannin,data=reg.data),col=\"cyan\",lwd=2)\n",
    "for (i in 1:9) {\n",
    "  lines(c(reg.data$tannin[i],reg.data$tannin[i]),c(reg.data$growth[i],fitted[i]),col=\"magenta\")\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Residuals show the difference between the prediction (the line here) and the actual values.  Notice that the residuals are vertical. This is because we are trying to predict the response variable (which is on the y-axis) given that we know the values of the explanatory variable ( on the x-axis)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Plot square residuals**<br/>\n",
    "Why is this line the \"best\" line?  It is best in a very specific sense.  It minimizes the sum of the squared residuals.  This is called a <i>least squares fit</i>.  In other words the regression line minimizes the quantity:\n",
    "$$\\sum_{i=1}^{i=n}(y_i-\\hat{y}_i)^2$$\n",
    "where $y_i$ is the actual response value and $\\hat{y}_i$ is the predicted value. <br/>\n",
    "Least squares fitting is a very common criterion for fitting a model to data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(reg.data$tannin,reg.data$growth,pch=21,bg=\"blue\",asp=1,xlab=\"tannin content\",ylab=\"growth\")\n",
    "abline(lm(growth~tannin,data=reg.data),col=\"cyan\",lwd=2)\n",
    "for (i in 1:9) {\n",
    "  lines(c(reg.data$tannin[i],reg.data$tannin[i]),c(reg.data$growth[i],fitted[i]),col=\"magenta\")\n",
    "res=abs(reg.data$growth[i]-fitted[i])\n",
    "    if (reg.data$growth[i]<fitted[i]) {#then square goes to left\n",
    "    lines(c(reg.data$tannin[i],reg.data$tannin[i]-res,reg.data$tannin[i]-res,reg.data$tannin[i]),c(reg.data$growth[i],reg.data$growth[i],fitted[i],fitted[i]),col=\"magenta\")\n",
    "    }\n",
    "    else {#then square goes to left\n",
    "    lines(c(reg.data$tannin[i],reg.data$tannin[i]+res,reg.data$tannin[i]+res,reg.data$tannin[i]),c(reg.data$growth[i],reg.data$growth[i],fitted[i],fitted[i]),col=\"magenta\")\n",
    "    }\n",
    "    }"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Estimating the line**<br/>\n",
    "This code shows the squared residuals for different slopes.  You can see it is a quadratic function concave downwards which means it has a single minimum (if you were to use summed absolute residuals instead of summed squared residuals you would not necessarily have a unique minimum).  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "b <-  seq(-1.43,-1,0.002)\n",
    "sse <- numeric(length(b))\n",
    "for (i in 1:length(b)) {\n",
    "  a <- mean(reg.data$growth)-b[i]*mean(reg.data$tannin)\n",
    "  residual <- reg.data$growth - a - b[i]*reg.data$tannin\n",
    "  sse[i] <- sum(residual^2)\n",
    "}\n",
    "mlval=b[which(sse==min(sse))]\n",
    "plot(b,sse,type=\"l\",ylim=c(19,24))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "b <-  seq(-1.43,-1,0.002)\n",
    "sse <- numeric(length(b))\n",
    "for (i in 1:length(b)) {\n",
    "  a <- mean(reg.data$growth)-b[i]*mean(reg.data$tannin)\n",
    "  residual <- reg.data$growth - a - b[i]*reg.data$tannin\n",
    "  sse[i] <- sum(residual^2)\n",
    "}\n",
    "mlval=b[which(sse==min(sse))]\n",
    "plot(b,sse,type=\"l\",ylim=c(19,24))\n",
    "arrows(mlval,min(sse),mlval,min(sse)-1,col=\"magenta\")\n",
    "abline(h=min(sse),col=\"cyan\",lty=2)\n",
    "lines(b,sse)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Sums of squares**<br/>\n",
    "The response value $y_i$ can be broken into three parts.  One part is the mean response ($\\bar{y})$.  One part is explained by the model $(\\hat{y}_i-\\bar{y})$.  The other part is the residual, or unexplained part."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(c(0,10),c(0,10),xlab=\"\",ylab=\"\",type=\"n\")\n",
    "abline(h=5,lty=2)\n",
    "lines(c(0,10),c(8,2))\n",
    "text(2,6.2,expression(hat(y) - bar(y)))\n",
    "text(2,8.45,expression(y - hat(y)))\n",
    "arrows(7,5,7,9.5,code=3,length=0.1)\n",
    "arrows(1,5,1,7.4,code=3,length=0.1)\n",
    "arrows(1,9.5,1,7.4,code=3,length=0.1)\n",
    "points(1,9.5,pch=16)\n",
    "text(8,7.4,expression(y - bar(y)))\n",
    "text(0.2,5,expression(bar(y)))\n",
    "text(.2,7.4,expression(hat(y)))\n",
    "text(.2,9.5,\"y\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Regression model**<br/>\n",
    "R can do hypothesis tests on the slope and intercept to see if they are significantly different from zero. What would it mean if the slope were zero?<br/><br/>\n",
    "One important number to notice in the output below is $R^2$, the <a href = \"https://en.wikipedia.org/wiki/Coefficient_of_determination\">Coefficient of determination</a>.  This is the fraction of the total variation in the response variable that is explained by variation in the explanatory variable.  This ranges between 0 and 1.  If it is zero, then variation in the explanatory variable doesn't explain any of the variation in the response variable - not a very good model.  If it is 1, then variation in the response variable is perfectly explained by variation in the explanatory variable - a great model!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = growth ~ tannin, data = reg.data)\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-2.4556 -0.8889 -0.2389  0.9778  2.8944 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)  11.7556     1.0408  11.295 9.54e-06 ***\n",
       "tannin       -1.2167     0.2186  -5.565 0.000846 ***\n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "Residual standard error: 1.693 on 7 degrees of freedom\n",
       "Multiple R-squared:  0.8157,\tAdjusted R-squared:  0.7893 \n",
       "F-statistic: 30.97 on 1 and 7 DF,  p-value: 0.0008461\n"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model <- lm(growth~tannin,data=reg.data)\n",
    "summary(model)\n",
    "#summary.aov(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(End of Section 1. [Return to top.](#Table-of-Contents))\n",
    "\n",
    "* * *\n",
    "\n",
    "## 2. Non-linear relationships\n",
    "**Particle decay**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "decay<-read.csv('shinyexample/decay.csv')\n",
    "decay"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Plot the data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plot(decay$time,decay$amount,pch=21,col=\"blue\",bg=\"cyan\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Linear fit**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plot(decay$time,decay$amount,pch=21,col=\"blue\",bg=\"cyan\")\n",
    "abline(lm(amount~time,data=decay),col=\"magenta\")\n",
    "linmodel=lm(amount~time,data=decay)\n",
    "summary(lm(amount~time,data=decay))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The linear fit is okay, but it really looks like the data itself doesn't follow a line."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Transform data** to make it more linear<br/>\n",
    "Instead of using the variable itself, work with a function of the variable (in this case the log of the response variable)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "ERROR",
     "evalue": "Error in plot(decay$time, log(decay$amount), pch = 21, col = \"blue\", bg = \"magenta\"): object 'decay' not found\n",
     "output_type": "error",
     "traceback": [
      "Error in plot(decay$time, log(decay$amount), pch = 21, col = \"blue\", bg = \"magenta\"): object 'decay' not found\n"
     ]
    },
    {
     "ename": "ERROR",
     "evalue": "Error in is.data.frame(data): object 'decay' not found\n",
     "output_type": "error",
     "traceback": [
      "Error in is.data.frame(data): object 'decay' not found\n"
     ]
    },
    {
     "ename": "ERROR",
     "evalue": "Error in is.data.frame(data): object 'decay' not found\n",
     "output_type": "error",
     "traceback": [
      "Error in is.data.frame(data): object 'decay' not found\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = growth ~ tannin, data = reg.data)\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-2.4556 -0.8889 -0.2389  0.9778  2.8944 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)  11.7556     1.0408  11.295 9.54e-06 ***\n",
       "tannin       -1.2167     0.2186  -5.565 0.000846 ***\n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "Residual standard error: 1.693 on 7 degrees of freedom\n",
       "Multiple R-squared:  0.8157,\tAdjusted R-squared:  0.7893 \n",
       "F-statistic: 30.97 on 1 and 7 DF,  p-value: 0.0008461\n"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot(decay$time,log(decay$amount),pch=21,col=\"blue\",bg=\"magenta\")\n",
    "abline(lm(log(amount)~time,data=decay),col=\"blue\")\n",
    "model <- lm(log(amount)~time,data=decay)\n",
    "summary(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the model against the raw data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plot(decay$time,decay$amount,pch=21,col=\"blue\",bg=\"cyan\")\n",
    "xv <- seq(0,30,0.25)\n",
    "yv <- exp(model$coefficients[1]) * exp(model$coefficients[2] * xv)\n",
    "lines(xv,yv,col=\"magenta\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The non-linear model looks like it fits better, but how can you prove this?  There are various statistics that can be used to compare models.  Common ones are comparing the log-likelihoods using a <a href = \"https://en.wikipedia.org/wiki/Likelihood-ratio_test\">likelihood ratio test</a> or various information criteria (<a href = \"https://en.wikipedia.org/wiki/Akaike_information_criterion\">AIC</a>, <a href = \"https://en.wikipedia.org/wiki/Bayesian_information_criterion\">BIC</a>)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\n",
    "AIC(linmodel,model)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(End of Section 2. [Return to top.](#Table-of-Contents))\n",
    "\n",
    "* * *\n",
    "\n",
    "## 3. Non-linear regression\n",
    "**Example 2**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "deer<-read.csv('shinyexample/jaws.csv')\n",
    "deer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plot(deer$age,deer$bone,pch=21,bg=\"lightgrey\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sometimes it is not possible to transform the data such that a linear model would fit it nicely. So you can use a non-linear model. In this example, we are comparing two possible non-linear models: $$(1)\\ \\ bone_i=a-b*e^{-c*age_i}$$ $$(2)\\ \\ bone_i=a-a*e^{-c*age_i}$$  The first has three parameters (a,b,c).  The second only has two (a,c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "model <- nls(bone~a-b*exp(-c*age),data=deer,start=list(a=120,b=110,c=0.064))\n",
    "summary(model)\n",
    "av <- seq(0,50,0.1)\n",
    "bv <- predict(model,list(age=av),data=deer)\n",
    "plot(deer$age,deer$bone,pch=21,bg=\"lightgrey\")\n",
    "lines(av,bv,col=\"blue\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "model2 <- nls(bone~a*(1-exp(-c*age)),data=deer,start=list(a=120,c=0.064))\n",
    "av2 <- seq(0,50,0.1)\n",
    "bv2 <- predict(model2,list(age=av2),data=deer)\n",
    "plot(deer$age,deer$bone,pch=21,bg=\"lightgrey\")\n",
    "lines(av,bv,col=\"blue\")\n",
    "lines(av2,bv2,col=\"magenta\")\n",
    "summary(model2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "AIC(model,model2)\n",
    "#anova(model,model2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(End of Section 3. [Return to top.](#Table-of-Contents))\n",
    "\n",
    "* * *\n",
    "\n",
    "## 4. Analysis of variance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "In file(file, \"rt\"): cannot open file 'shinyexample/oneway.csv': No such file or directory"
     ]
    },
    {
     "ename": "ERROR",
     "evalue": "Error in file(file, \"rt\"): cannot open the connection\n",
     "output_type": "error",
     "traceback": [
      "Error in file(file, \"rt\"): cannot open the connection\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>ozone</th><th scope=col>garden</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>3</td><td>A</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>5</td><td>B</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>4</td><td>A</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>5</td><td>B</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>4</td><td>A</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>6</td><td>B</td></tr>\n",
       "\t<tr><th scope=row>7</th><td>3</td><td>A</td></tr>\n",
       "\t<tr><th scope=row>8</th><td>7</td><td>B</td></tr>\n",
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       "\t<tr><th scope=row>11</th><td>3</td><td>A</td></tr>\n",
       "\t<tr><th scope=row>12</th><td>4</td><td>B</td></tr>\n",
       "\t<tr><th scope=row>13</th><td>1</td><td>A</td></tr>\n",
       "\t<tr><th scope=row>14</th><td>3</td><td>B</td></tr>\n",
       "\t<tr><th scope=row>15</th><td>3</td><td>A</td></tr>\n",
       "\t<tr><th scope=row>16</th><td>5</td><td>B</td></tr>\n",
       "\t<tr><th scope=row>17</th><td>5</td><td>A</td></tr>\n",
       "\t<tr><th scope=row>18</th><td>6</td><td>B</td></tr>\n",
       "\t<tr><th scope=row>19</th><td>2</td><td>A</td></tr>\n",
       "\t<tr><th scope=row>20</th><td>5</td><td>B</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       "  & ozone & garden\\\\\n",
       "\\hline\n",
       "\t1 & 3 & A\\\\\n",
       "\t2 & 5 & B\\\\\n",
       "\t3 & 4 & A\\\\\n",
       "\t4 & 5 & B\\\\\n",
       "\t5 & 4 & A\\\\\n",
       "\t6 & 6 & B\\\\\n",
       "\t7 & 3 & A\\\\\n",
       "\t8 & 7 & B\\\\\n",
       "\t9 & 2 & A\\\\\n",
       "\t10 & 4 & B\\\\\n",
       "\t11 & 3 & A\\\\\n",
       "\t12 & 4 & B\\\\\n",
       "\t13 & 1 & A\\\\\n",
       "\t14 & 3 & B\\\\\n",
       "\t15 & 3 & A\\\\\n",
       "\t16 & 5 & B\\\\\n",
       "\t17 & 5 & A\\\\\n",
       "\t18 & 6 & B\\\\\n",
       "\t19 & 2 & A\\\\\n",
       "\t20 & 5 & B\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "   ozone garden\n",
       "1      3      A\n",
       "2      5      B\n",
       "3      4      A\n",
       "4      5      B\n",
       "5      4      A\n",
       "6      6      B\n",
       "7      3      A\n",
       "8      7      B\n",
       "9      2      A\n",
       "10     4      B\n",
       "11     3      A\n",
       "12     4      B\n",
       "13     1      A\n",
       "14     3      B\n",
       "15     3      A\n",
       "16     5      B\n",
       "17     5      A\n",
       "18     6      B\n",
       "19     2      A\n",
       "20     5      B"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oneway<-read.csv('shinyexample/oneway.csv')\n",
    "oneway"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(1:20,oneway$ozone,ylim=c(0,8),ylab=\"ozone\",xlab=\"individual datapoints\",pch=21,bg=\"magenta\")\n",
    "abline(h=mean(oneway$ozone),col=\"blue\")\n",
    "for(i in 1:20) lines(c(i,i),c(mean(oneway$ozone),oneway$ozone[i]),col=\"cyan\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What if your explanatory variable is categorical?  Think about the situation where you measure some quantitative response variable on different groups and want to know how group membership affects the response variable. These groups could be treatments (drug, no drug) or plots (fertilized, watered, shaded, etc.) or whatever.  We want to know what effect each treatment has.  We express those as deviations from the mean.  In the plot above, the overall mean is the blue line and the deviations are marked in cyan."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(1:20,oneway$ozone,ylim=c(0,8),xlim=c(1,21),ylab=\"ozone\",xlab=\"individual datapoints\",\n",
    "     pch=21,bg=as.numeric(oneway$garden))\n",
    "## 5f ##\n",
    "abline(h=mean(oneway$ozone[oneway$garden==\"A\"]))\n",
    "abline(h=mean(oneway$ozone[oneway$garden==\"B\"]),col=\"red\")\n",
    "index <- 1:length(oneway$ozone)\n",
    "for (i in 1:length(index)){\n",
    "  if (oneway$garden[i] == \"A\" )\n",
    "    lines(c(index[i],index[i]),c(mean(oneway$ozone[oneway$garden==\"A\"]),oneway$ozone[i]))\n",
    "  else \n",
    "    lines(c(index[i],index[i]),c(mean(oneway$ozone[oneway$garden==\"B\"]),oneway$ozone[i]), col=\"red\")\n",
    "}\n",
    "\n",
    "arrows(21,mean(oneway$ozone),21,mean(oneway$ozone[oneway$garden==\"A\"]),col=\"black\",length=.1)\n",
    "      arrows(21,mean(oneway$ozone),21,mean(oneway$ozone[oneway$garden==\"B\"]),col=\"red\",length=.1)\n",
    "      points(21,mean(oneway$ozone),pch=19,col=\"blue\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The red line in the plot is the mean ozone for the red group (B). The black line is the mean ozone for the black group. Notice that the residuals are smaller.  By breaking the data apart into groups, we have reduced the unexplained variation in ozone levels.  The arrows show the deviations of the group means from the overall means and represent the effect of being in the red or black group."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "            Df Sum Sq Mean Sq F value  Pr(>F)   \n",
       "garden       1     20  20.000      15 0.00111 **\n",
       "Residuals   18     24   1.333                   \n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary(aov(ozone~garden,data=oneway))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(End of Section 4. [Return to top.](#Table-of-Contents))\n",
    "\n",
    "* * *\n",
    "\n",
    "## 5. ANCOVA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "In file(file, \"rt\"): cannot open file 'shinyexample/ipomopsis.csv': No such file or directory"
     ]
    },
    {
     "ename": "ERROR",
     "evalue": "Error in file(file, \"rt\"): cannot open the connection\n",
     "output_type": "error",
     "traceback": [
      "Error in file(file, \"rt\"): cannot open the connection\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Root</th><th scope=col>Fruit</th><th scope=col>Grazing</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>6.225</td><td>59.77</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>6.487</td><td>60.98</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>4.919</td><td>14.73</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>5.13</td><td>19.28</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>5.417</td><td>34.25</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>5.359</td><td>35.53</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>7</th><td>7.614</td><td>87.73</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>8</th><td>6.352</td><td>63.21</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>9</th><td>4.975</td><td>24.25</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>10</th><td>6.93</td><td>64.34</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>11</th><td>6.248</td><td>52.92</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>12</th><td>5.451</td><td>32.35</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>13</th><td>6.013</td><td>53.61</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>14</th><td>5.928</td><td>54.86</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>15</th><td>6.264</td><td>64.81</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>16</th><td>7.181</td><td>73.24</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>17</th><td>7.001</td><td>80.64</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>18</th><td>4.426</td><td>18.89</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>19</th><td>7.302</td><td>75.49</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>20</th><td>5.836</td><td>46.73</td><td>Ungrazed</td></tr>\n",
       "\t<tr><th scope=row>21</th><td>10.253</td><td>116.05</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>22</th><td>6.958</td><td>38.94</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>23</th><td>8.001</td><td>60.77</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>24</th><td>9.039</td><td>84.37</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>25</th><td>8.91</td><td>70.11</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>26</th><td>6.106</td><td>14.95</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>27</th><td>7.691</td><td>70.7</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>28</th><td>8.988</td><td>80.31</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>29</th><td>8.975</td><td>82.35</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>30</th><td>9.844</td><td>105.07</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>31</th><td>8.508</td><td>73.79</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>32</th><td>7.354</td><td>50.08</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>33</th><td>8.643</td><td>78.28</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>34</th><td>7.916</td><td>41.48</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>35</th><td>9.351</td><td>98.47</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>36</th><td>7.066</td><td>40.15</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>37</th><td>8.158</td><td>52.26</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>38</th><td>7.382</td><td>46.64</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>39</th><td>8.515</td><td>71.01</td><td>Grazed</td></tr>\n",
       "\t<tr><th scope=row>40</th><td>8.53</td><td>83.03</td><td>Grazed</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lll}\n",
       "  & Root & Fruit & Grazing\\\\\n",
       "\\hline\n",
       "\t1 & 6.225 & 59.77 & Ungrazed\\\\\n",
       "\t2 & 6.487 & 60.98 & Ungrazed\\\\\n",
       "\t3 & 4.919 & 14.73 & Ungrazed\\\\\n",
       "\t4 & 5.13 & 19.28 & Ungrazed\\\\\n",
       "\t5 & 5.417 & 34.25 & Ungrazed\\\\\n",
       "\t6 & 5.359 & 35.53 & Ungrazed\\\\\n",
       "\t7 & 7.614 & 87.73 & Ungrazed\\\\\n",
       "\t8 & 6.352 & 63.21 & Ungrazed\\\\\n",
       "\t9 & 4.975 & 24.25 & Ungrazed\\\\\n",
       "\t10 & 6.93 & 64.34 & Ungrazed\\\\\n",
       "\t11 & 6.248 & 52.92 & Ungrazed\\\\\n",
       "\t12 & 5.451 & 32.35 & Ungrazed\\\\\n",
       "\t13 & 6.013 & 53.61 & Ungrazed\\\\\n",
       "\t14 & 5.928 & 54.86 & Ungrazed\\\\\n",
       "\t15 & 6.264 & 64.81 & Ungrazed\\\\\n",
       "\t16 & 7.181 & 73.24 & Ungrazed\\\\\n",
       "\t17 & 7.001 & 80.64 & Ungrazed\\\\\n",
       "\t18 & 4.426 & 18.89 & Ungrazed\\\\\n",
       "\t19 & 7.302 & 75.49 & Ungrazed\\\\\n",
       "\t20 & 5.836 & 46.73 & Ungrazed\\\\\n",
       "\t21 & 10.253 & 116.05 & Grazed\\\\\n",
       "\t22 & 6.958 & 38.94 & Grazed\\\\\n",
       "\t23 & 8.001 & 60.77 & Grazed\\\\\n",
       "\t24 & 9.039 & 84.37 & Grazed\\\\\n",
       "\t25 & 8.91 & 70.11 & Grazed\\\\\n",
       "\t26 & 6.106 & 14.95 & Grazed\\\\\n",
       "\t27 & 7.691 & 70.7 & Grazed\\\\\n",
       "\t28 & 8.988 & 80.31 & Grazed\\\\\n",
       "\t29 & 8.975 & 82.35 & Grazed\\\\\n",
       "\t30 & 9.844 & 105.07 & Grazed\\\\\n",
       "\t31 & 8.508 & 73.79 & Grazed\\\\\n",
       "\t32 & 7.354 & 50.08 & Grazed\\\\\n",
       "\t33 & 8.643 & 78.28 & Grazed\\\\\n",
       "\t34 & 7.916 & 41.48 & Grazed\\\\\n",
       "\t35 & 9.351 & 98.47 & Grazed\\\\\n",
       "\t36 & 7.066 & 40.15 & Grazed\\\\\n",
       "\t37 & 8.158 & 52.26 & Grazed\\\\\n",
       "\t38 & 7.382 & 46.64 & Grazed\\\\\n",
       "\t39 & 8.515 & 71.01 & Grazed\\\\\n",
       "\t40 & 8.53 & 83.03 & Grazed\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "     Root  Fruit  Grazing\n",
       "1   6.225  59.77 Ungrazed\n",
       "2   6.487  60.98 Ungrazed\n",
       "3   4.919  14.73 Ungrazed\n",
       "4   5.130  19.28 Ungrazed\n",
       "5   5.417  34.25 Ungrazed\n",
       "6   5.359  35.53 Ungrazed\n",
       "7   7.614  87.73 Ungrazed\n",
       "8   6.352  63.21 Ungrazed\n",
       "9   4.975  24.25 Ungrazed\n",
       "10  6.930  64.34 Ungrazed\n",
       "11  6.248  52.92 Ungrazed\n",
       "12  5.451  32.35 Ungrazed\n",
       "13  6.013  53.61 Ungrazed\n",
       "14  5.928  54.86 Ungrazed\n",
       "15  6.264  64.81 Ungrazed\n",
       "16  7.181  73.24 Ungrazed\n",
       "17  7.001  80.64 Ungrazed\n",
       "18  4.426  18.89 Ungrazed\n",
       "19  7.302  75.49 Ungrazed\n",
       "20  5.836  46.73 Ungrazed\n",
       "21 10.253 116.05   Grazed\n",
       "22  6.958  38.94   Grazed\n",
       "23  8.001  60.77   Grazed\n",
       "24  9.039  84.37   Grazed\n",
       "25  8.910  70.11   Grazed\n",
       "26  6.106  14.95   Grazed\n",
       "27  7.691  70.70   Grazed\n",
       "28  8.988  80.31   Grazed\n",
       "29  8.975  82.35   Grazed\n",
       "30  9.844 105.07   Grazed\n",
       "31  8.508  73.79   Grazed\n",
       "32  7.354  50.08   Grazed\n",
       "33  8.643  78.28   Grazed\n",
       "34  7.916  41.48   Grazed\n",
       "35  9.351  98.47   Grazed\n",
       "36  7.066  40.15   Grazed\n",
       "37  8.158  52.26   Grazed\n",
       "38  7.382  46.64   Grazed\n",
       "39  8.515  71.01   Grazed\n",
       "40  8.530  83.03   Grazed"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ancdata<-read.csv('shinyexample/ipomopsis.csv')\n",
    "ancdata"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(ancdata$Root,ancdata$Fruit,pch=16,col=\"blue\",xlab='Root size',ylab='Fruit')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you look at the data, you see that there is another variable.  In fact, there are two explanatory variables (one quantitative, one categorical) and one response variable (quantitative) in this example."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another view of the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(ancdata$Grazing,ancdata$Fruit,col=\"lightgreen\",ylab=\"Fruit\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From this plot (which does not include root size) it looks like grazing increases fruit yield."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Model:  fruit depends on grazing status:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = Fruit ~ Grazing, data = ancdata)\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-52.991 -18.028   2.915  14.050  48.110 \n",
       "\n",
       "Coefficients:\n",
       "                Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)       67.941      5.236  12.976 1.54e-15 ***\n",
       "GrazingUngrazed  -17.060      7.404  -2.304   0.0268 *  \n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "Residual standard error: 23.41 on 38 degrees of freedom\n",
       "Multiple R-squared:  0.1226,\tAdjusted R-squared:  0.09949 \n",
       "F-statistic: 5.309 on 1 and 38 DF,  p-value: 0.02678\n"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "justGrazingModel=lm(Fruit~Grazing,data=ancdata)\n",
    "summary(justGrazingModel)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What about root size?\n",
    "<br/>\n",
    "In this model, fruit size depends on both root size and grazing group and the effect of root size on fruit size could differ between grazing groups."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fullmodel <- lm(Fruit~Root*Grazing,data=ancdata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "summary.aov(fullmodel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "AIC(justGrazingModel,fullmodel)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Model without interaction<br/>\n",
    "In this model, fruit size depends on both root size and grazing group <u>but</u> the effect of root size on fruit size is the same regardless of grazing group."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "noInteractionModel=lm(Fruit~Grazing+Root,data=ancdata)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "anova(noInteractionModel,fullmodel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plot(ancdata$Root,ancdata$Fruit,pch=21,bg=(4*as.numeric(ancdata$Grazing)))\n",
    "legend(\"topleft\",c(\"grazed\",\"ungrazed\"),col=c(4,8),pch=16)\n",
    "abline(-127.829,23.56,col=\"blue\")\n",
    "abline(-127.829+36.103,23.56,col=\"blue\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(End of Section 5. End of Module 2. [Return to top.](#Table-of-Contents))\n",
    "\n",
    "* * *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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