Links and recommendations

A collection of things that I find myself sharing often.

Resources for learning programming and data analysis

• The Missing Semester of your Computer Science Education, an open course from MIT covering tools like shell scripting, text editors, and git--all of which can make your programming and computing life easier, but which tend to be overlooked in typical classroom settings.

• R for Data Science by Grolemund and Wickham. Free!

• Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan by Kruschke.

• Putting it all together with Knitr, LaTeX, and R Markdown. Materials from the 2019 LSA Institute workshop by McDonnell and Rentz.

Crowdsourcing platforms

• I've had a good experience recruiting participants via Prolific. (If you sign up via that referral link, we both get a bit of money.)

Job Advice

• The Professor Is In: The Essential Guide To Turning Your Ph.D. Into a Job by Kelsky. The ultimate guide to the academic job search.

• Advice on finding a post-doc by Tal Linzen.