8x3_lab01.pdf - \"cells\"cell_type\"markdown\"metadata\"source Lab 1 Variance of Sample Means and Correlation\\n\\n\"Welcome to Lab 1 and Data 8.3x\\n\\n\"In this

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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Lab 1: Variance of Sample Means and Correlation\n", "\n", "Welcome to Lab 1 and Data 8.3x!\n", "\n", "In this lab we will learn about [the variance of sample means] (- sample-mean.html) as well as ways to understand and quantify [the association between two variables](https:// )." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# Run this cell, but please don't change it.\n", "\n", "# These lines import the Numpy and Datascience modules.\n", "import numpy as np\n", "from datascience import *\n", "\n", "# These lines do some fancy plotting magic.\n", "import matplotlib\n", "%matplotlib inline\n", "import matplotlib.pyplot as plots\n", "plots.style.use('fivethirtyeight')\n", "import warnings\n", "warnings.simplefilter('ignore', FutureWarning)\n", "warnings.simplefilter('ignore', UserWarning)\n", "\n", "# These lines load the tests.\n", "from gofer.ok import check" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1. How Faithful is Old Faithful? \n", "\n", "(Note: clever title comes from [here]( ~jfreder/M212/oldfaithful.pdf).)\n",
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"\n", "Old Faithful is a geyser in Yellowstone National Park in the central United States. It's famous for erupting on a fairly regular schedule. You can see a video below." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "image/jpeg": "/9j/4AAQSkZJRgABAQAAAQABAAD/ 2wCEABALDA4MChAODQ4SERATGCgaGBYWGDEjJR0oOjM9PDkzODdASFxOQERXRTc4UG1RV1 9iZ2hnPk1xeXBkeFxlZ2MBERISGBUYLxoaL2NCOEJjY2NjY2NjY2NjY2NjY2NjY2NjY2Nj Y2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY//AABEIAWgB4AMBIgACEQEDEQH/ xAAbAAEAAwEBAQEAAAAAAAAAAAAAAQIDBQQGB// EAD4QAAICAQICBQkHAgUFAQAAAAABAhEDBCESMQVBUZLRExYiMlNhcYGRBhQVQkNS0jOhY nKCweEXI0RU8Af/xAAYAQEBAQEBAAAAAAAAAAAAAAAAAQIDBP/ EAB0RAQEBAAIDAQEAAAAAAAAAAAABEQISAyExURP/2gAMAwEAAhEDEQA/ APz8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAHU/AdV7TD9X4E/ gGq9ph+r8DXWpscoHV839X7TD9X4D8A1ftMP1fgOtNjlA6v4BqvaYfq/ ALoDVP9TD3n4Dpy/DtHKB1l9ntW/ 1MHefgT5u6v2mDvPwHWmxyAdfzc1ntMHefgPNzWe0wd5+BOtNcgHZX2a1j/ Uwd5+BZfZfWv9XT96XgMquIDur7J65/q6bvS8Cy+yHSD/W03el/ Ei44APol9jekX+tpe9L+JPmX0j7bS96X8SaY+cB9H5l9Je20vfl/EnzK6S9vpO/ L+I0yvmwfSeZXSXt9J35fxC+xPST/AF9J35fxGmV82D6XzI6S9vpO/L+I8yOk/b6Tvy/ iNhlfNA+l8x+k/b6Tvy/iSvsP0m/19J35fxGwyvmQfUL7B9KP9fR9+X8SV9gulH/ 5Gj78v4jYZXywPq/+n/Sv/saLvz/iQ/sB0qv/ ACNF35fxGwyvlQfUP7CdKL9fR9+X8SPMTpT2+j78v4jYZXzAPp/MXpP2+k78v4keY/ Sft9J35fxGwyvmQfTr7C9Jv9fSd+X8Sy+wfSj/ AF9H35fxGwyvlgfUv7A9KrnqNH35fxLx/wDz3paStajRd+f8RsMr5MH1v/Tzpb/2NF35/ wAR/wBPOlv/AGNF35/ xGwyvkgfT5vsL0nhVy1Gj+U5fxPFL7M62Lp5dP3n4GpLfiX19cUHY829Z7TB3n4Dzb1ntM Hefga/ny/Ge/Fxwdjzb1ntMHefgT5taz2mDvPwH8+X4d+LjA7Pm1rPa4O8/ AebWs9pg7z8B/Pl+Hfi4wOz5taz2uDvPwHm1rPa4O8/Afz5fh2jjA7Pm1rPa4O8/ AebWs9rg7z8B/ Pl+HaOMDs+bWs9rg7z8B5taz2uDvPwH8+X4do4wOz5taz2uDvPwHm1rPa4O8/ Afz5fh2jjA7Pm1rfaYO8/AebWt9rg7z8B/ Pl+HaOMDs+bOt9rg7z8B5s632uDvPwH8+X4do4wO15s632un7z8B5s632un7z8B/ Pl+HaO4gED0OSyYIBMNSEgSaiFk2QiSUiyZYrE0iYrcWijaBnEutjnXSN4msTCDNonOukb
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