Below is a list of books and materials I use across my courses.
If you are a Duke student, you may have access to electronic copies of these books (those not already available online for free) via Duke library.
- Agresti, A. (2013), “Categorical Data Analysis (3rd ed).”
- Albert, J. (2009), “Bayesian Computation with R (Second Edition).”
- Bolstad, W. M. and Curran, J. M. (2016), “Introduction to Bayesian Statistics (Third Edition).”
- Gelman, A., Carlin, J., Stern, H., Dunson, D., Vehtari, A., and Rubin, D., “Bayesian Data Analysis (Third Edition).”
- Gelman A., and Hill, J., “Data Analysis Using Regression and Multilevel/Hierarchical Models.”
- Hoff, P. D. (2009), “A First Course in Bayesian Statistical Methods.”
- Imbens, G. W. and Rubin, D. B. (2015), “Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction.”
- James, G., Witten, D., Hastie, T., and Tibshirani, R., “An Introduction to Statistical Learning with Applications in R.”
- Ramsey, F.L. and Schafer, D.W. (2013), “The Statistical Sleuth: A Course in Methods of Data Analysis (3rd ed).”
R and R Markdown Resources
R Markdown can be used to create high quality reports and presentations with embedded chunks of R code. To learn more about R Markdown and for other resources for programming in R, see the links below.
- A very basic R Markdown template
- Data Visualization with ggplot2 Cheat Sheet
- Introduction to R Markdown (Article by Garrett Grolemund)
- Introduction to R Markdown (Slides by Andrew Cho)
- Other Useful Cheat Sheets
- R for Data Science (by Hadley Wickham & Garrett Grolemund)
- R Markdown Cheat Sheet
LaTeX is another very useful tool. 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.
These are articles I find interesting as supplementary readings for topics covered in my courses.
- A Dirty Dozen: Twelve P-Value Misconceptions (by Steven Goodman)
- American Statistical Association Statement on P-values