Editing Data Into Insights (Spring 2021) (section)

== Readings ==

* Required texts:
**  '''Data Visualization: A Practical Introduction''' by Kieran Healy. [https://socviz.co/index.html Web version (free!)] or [https://amzn.to/2vfAixM Print version (Amazon)]
** '''R for Data Science''' by Hadley Wickham and Garrett Grolemund. [https://r4ds.had.co.nz/index.html Web version (free!)] or [http://amzn.to/2aHLAQ1 Print version (Amazon)]
** '''Effective Data Storytelling''' by Brent Dykes. [https://purdue-primo-prod.hosted.exlibrisgroup.com/permalink/f/vjfldl/PURDUE_ALMA51860241510001081 Purdue libraries] or [https://smile.amazon.com/dp/1119615712 Print version (Amazon)]

* Other readings: Readings will be linked to from this page. Where necessary, they will be put on Brightspace

=== Reading Academic Articles ===

Some of the readings will be academic articles. I do not expect you to read every word of these articles. Rather, you should practice intentional directed skimming. [https://writingcenter.gmu.edu/guides/strategies-for-reading-academic-articles This article] gives a nice overview. The TL;DR is that you should carefully read the abstract, introduction, and conclusion. For the rest of the article, focus on section headings and topic sentences to extract the main ideas.