Supplementary Textbooks

These textbooks are great resources for some of the topics we will cover. You do not need to buy them, but you may be able to borrow them from Duke library should you need extra reading materials, besides the class slides and main textbooks. I may also select and adapt questions from the books for your homework assignments from time to time, but you will not need access to them when I do so.

  1. Ramsey, F.L. and Schafer, D.W. (2013), "The Statistical Sleuth: A Course in Methods of Data Analysis (3rd ed)".
  2. Imbens, G. W. and Rubin, D. B. (2015), "Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction".
  3. R for Data Science (by Hadley Wickham & Garrett Grolemund).

R and R Markdown Resources

R Markdown can be used to create high quality reports and presentations with embedded chunks of R code. You are required to use R Markdown to type up your lab reports. R Markdown would also be my personal favorite for typing up your homework assignments and project write-ups for this course, but you are welcome to use any word processor of your choice for those. To learn more about R Markdown and for other resources for programming in R, see the links below.

  1. Introduction to R Markdown (Article by Garrett Grolemund)
  2. Introduction to R Markdown (Slides by Andrew Cho)
  3. R Markdown Cheat Sheet
  4. Data Visualization with ggplot2 Cheat Sheet
  5. Other Useful Cheat Sheets
  6. A very (very!) basic R Markdown template


You may also use LaTeX to create your reports and presentations. You may find it easier to create your TeX and LaTeX documents using online editors such as Overleaf (simply create a free account and you are good to go!). However, that need not be the case. If you prefer to create them locally/offline on your personal computers, you will need to download a TeX distribution (the most popular choices are MiKTeX for Windows and MacTeX for macOS) plus an editor (I personally prefer TeXstudio but feel free to download any editor of your choice). Follow the links below for some options, and to also learn how to use LaTeX.

  1. Learn LaTeX in 30 minutes
  2. Choosing a LaTeX Compiler.

Interesting Articles

These are articles I find interesting either as supplementary readings for topics covered in class, or as good sources that cover concepts I think you should know, but which we may not have time to cover. I strongly suggest you find time to (at the very least) take a "quick peek" at each article.

  1. A Dirty Dozen: Twelve P-Value Misconceptions (by Steven Goodman)
  2. American Statistical Association Statement on P-values