<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Data 100: Principles and Techniques of Data Science on</title><link>https://notes.bencuan.me/data100/</link><description>Recent content in Data 100: Principles and Techniques of Data Science on</description><generator>Hugo</generator><language>en</language><atom:link href="https://notes.bencuan.me/data100/index.xml" rel="self" type="application/rss+xml"/><item><title/><link>https://notes.bencuan.me/data100/The-Data-100-Cheat-Sheet/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://notes.bencuan.me/data100/The-Data-100-Cheat-Sheet/</guid><description>&lt;h1 id="the-data-100-cheat-sheet"&gt;
 The Data 100 Cheat Sheet
 &lt;a class="anchor" href="#the-data-100-cheat-sheet"&gt;#&lt;/a&gt;
&lt;/h1&gt;
&lt;p&gt;Created: December 14, 2020 8:49 AM
Last Edited: December 22, 2020 7:41 PM&lt;/p&gt;
&lt;h1 id="resources"&gt;
 Resources
 &lt;a class="anchor" href="#resources"&gt;#&lt;/a&gt;
&lt;/h1&gt;
&lt;p&gt;&lt;strong&gt;Textbook:&lt;/strong&gt; 
&lt;a href="http://www.textbook.ds100.org/ch/01/lifecycle_intro.html" rel="noopener"&gt;http://www.textbook.ds100.org/ch/01/lifecycle_intro.html&lt;/a&gt;&lt;/p&gt;
&lt;h1 id="pandas-cheat-sheet"&gt;
 Pandas Cheat Sheet
 &lt;a class="anchor" href="#pandas-cheat-sheet"&gt;#&lt;/a&gt;
&lt;/h1&gt;
&lt;p&gt;[[The Data 100 Cheat Sheet 69de92fa14684dd1b94defbbb8983019 Pandas_Cheat_Sheet.pdf]]&lt;/p&gt;
&lt;h1 id="data-science-lifecycle"&gt;
 Data Science Lifecycle
 &lt;a class="anchor" href="#data-science-lifecycle"&gt;#&lt;/a&gt;
&lt;/h1&gt;
&lt;p&gt;![[/data100/img/Untitled.png]]&lt;/p&gt;
&lt;p&gt;
&lt;a href="http://www.ds100.org/fa20/lecture/lec01/" rel="noopener"&gt;http://www.ds100.org/fa20/lecture/lec01/&lt;/a&gt;&lt;/p&gt;
&lt;h1 id="data-sampling"&gt;
 Data Sampling
 &lt;a class="anchor" href="#data-sampling"&gt;#&lt;/a&gt;
&lt;/h1&gt;
&lt;p&gt;
&lt;a href="https://docs.google.com/presentation/d/1pI4shcpHeNU9vjOaG9l7cYfPe4GWy6hXICpQR8zTH1A/edit#slide=id.g8960eb33b8_0_151" rel="noopener"&gt;https://docs.google.com/presentation/d/1pI4shcpHeNU9vjOaG9l7cYfPe4GWy6hXICpQR8zTH1A/edit#slide=id.g8960eb33b8_0_151&lt;/a&gt;&lt;/p&gt;
&lt;h2 id="types-of-samples"&gt;
 Types of Samples
 &lt;a class="anchor" href="#types-of-samples"&gt;#&lt;/a&gt;
&lt;/h2&gt;
&lt;p&gt;A &lt;strong&gt;convenience sample&lt;/strong&gt; is whoever you can get ahold of.&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Not a good idea for inference!&lt;/li&gt;
&lt;li&gt;Haphazard ≠ random.&lt;/li&gt;
&lt;li&gt;Sources of bias can introduce themselves in ways you may not think of!&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;In a &lt;strong&gt;quota sample&lt;/strong&gt;, you first specify your desired breakdown of various subgroups, and then reach those targets however you can.&lt;/p&gt;</description></item></channel></rss>