September 23, 2016 •Eva Palmer
Even data scientists need a little downtime, and sometimes the best break from a day full of computer programs and spreadsheets is to curl up with a good book. We broke down some of our favorite reads:
The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century by David Salsburg
This book follows the theories of men and women who revolutionized the science field through the application of statistics. David Salsburg tells the stories of statisticians like Ronald Fisher, who tested an important hypothesis with inspiration from a tea party, and others who made important scientific breakthroughs.
R for Data Science by Hadley Wickham
Need to brush up on your R? Looking to get into the "grammar of graphics"? Hadley Wickham's book is perfect for data scientists who want to refresh their R skills or learn a new one.
The Signal and the Noise: Why So Many Predictions Fail - But Some Don't by Nate Silver
Any data scientist will tell you that using data and statistics to predict events and outcomes is a tricky business. Nate Silver, of FiveThirtyEight fame, penned The Signal and the Noise on the art of prediction and why human nature causes some forecasts to go south.
Advanced Statistics from an Elementary Point of View by Cosma Shalizi
This textbook, available for free online, dives into more advanced data analysis techniques. Cosma Shalizi breaks down complex concepts and makes them easy to understand.
Thing Explainer: Complicated Stuff in Simple Words by Randall Monroe
An important part of any science is breaking down complicated details into simple concepts. Data scientists will love Thing Explainer, where author Randall Monroe explains anything from microwaves to data centers using only cartoons and the thousand most common words in the English language.
Our Data Science Club helped put these suggestions together. Have more? Find us on Twitter (@summitdistrict) and let us know!
