CommunityData:StatsGaps

DRAFT -- IN PROGRESS -- IGNORE

Welcome to the StatsGaps page -- a set of suggested learning pathways making use of course resources produced by community data faculty, meant to be used by folks who have a mixture of familiarity and non-familiarity with R, statistics, and research processes.

This can all be done at no cost -- the primary text is free, and UW is subscribed to an online copy of the Verzani book here: [[1]].

Follow the strand(s) that apply to you:

• Learn R (you don't know R)
• Learn Stats (you haven't taken much if any statistics, or otherwise feel you're mostly starting from scratch)
• Refresh -- overview and shore up your stats knowledge if it feels rusty
• Strong Getting Stronger (your stats knowledge is strong but your class stopped before you got to good stuff you see used in lots of the papers in this group, like regression)

Week 1

All:

• Kramer, Adam D. I., Jamie E. Guillory, and Jeffrey T. Hancock. 2014. Experimental Evidence of Massive-Scale Emotional Contagion through Social Networks. Proceedings of the National Academy of Sciences 111(24):8788–90. [Open Access] If you haven't read this, you should--also, check the 'Editorial expression of concern' at the top and toss "kramer guillory hancock 2014" if you want to see the firestorm that this article created.-khc

Learn R:

• Week 1 R lecture materials (.zip file)
• Week 1 screencast (part 1, 23 minutes) (the video should load directly in browser window)
• Week 1 screencast (part 2, 27 minutes)

Learn Stats:

• Diez, Barr, and Çetinkaya-Rundel: §1 (Introduction to data)
• [Do Problem Set 1]

Refresh:

• Diez, Barr, and Çetinkaya-Rundel: §1 (Introduction to data)
• [Read Problem Set 1]

Stronger:

• [Skim Problem Set 1] -- since we may discuss it f2f.

• Verzani: §1 (Getting Started), §2 (Univariate data)
• Verzani: §A (Programming)
• Healy: §2 (and skim the preferatory material as well as §1)

Resources:

• Mine Çetinkaya-Rundel's OpenIntro §1 Lecture Notes
• OpenIntro Video Lectures including some for §1