{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Way number eight of looking at the correlation coefficient\n", "\n", "This is a notebook to accompany the blog post [\"Way number eight of looking at the correlation coefficient\"](http://composition.al/blog/2019/01/31/way-number-eight-of-looking-at-the-correlation-coefficient/). Read the post for additional context!" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "from datascience import *\n", "from datetime import *\n", "import matplotlib\n", "%matplotlib inline\n", "import matplotlib.pyplot as plots\n", "from mpl_toolkits.mplot3d import Axes3D\n", "import pandas as pd\n", "import math" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Recap from last time\n", "\n", "As [before](http://composition.al/blog/2018/08/31/understanding-the-regression-line-with-standard-units/), we're using the [datascience](http://data8.org/datascience/) package, and everything else we're using is pretty standard.\n", "\n", "And, as before, here's the data we'll be working with, [converted to standard units](https://www.inferentialthinking.com/chapters/14/2/Variability#standard-units) and plotted:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Date Height (standard units) Weight (standard units)
07/28/2017 -1.26135 -1.3158
08/07/2017 -1.08691 -1.13054
08/25/2017 -0.912464 -0.808628
09/25/2017 -0.228116 -0.399485
11/28/2017 0.107349 0.254728
01/26/2018 0.617255 0.728253
04/27/2018 1.12716 1.2537
07/30/2018 1.63707 1.41777