Resources

.bib file of all references

Books we’ll read

Statistical Rethinking

Richard McElreath, Statistical Rethinking: A Bayesian Course with Examples in R and Stan (McElreath 2020)

Official links:

• Book page
• R package
• 2022 lecture videos
• 2022 lecture slides and homework and answers

Translations:

• A. Solomon Kurz, Statistical Rethinking with brms, ggplot2, and the tidyverse: Second edition (Kurz 2021)
• Jake Thompson, Statistical Rethinking: Solutions (2nd edition)
• Vincent Arel-Bundock, Statistical Rethinking 2 with Stan and R, (Arel-Bundock 2020)

Bayes Rules

Alicia A. Johnson,, Miles Q. Ott, and Mine Dogucu. Bayes Rules! An Introduction to Applied Bayesian Modeling (Johnson, Ott, and Dogucu 2022)

Official links:

• Book page (and the entire book itself)
• Project page
• Teaching resources
• R package and package documentation
• Alicia Johnson, “Bayes Rules! An Introduction to Bayesian Modeling with R with Alicia Johnson”, presentation for R-Ladies Philly on October 18, 2021

Articles we’ll read

• Kruschke, John K., and Torrin M. Liddell. “The Bayesian New Statistics: Hypothesis Testing, Estimation, Meta-Analysis, and Power Analysis from a Bayesian Perspective” (Kruschke and Liddell 2018)
• Kruschke, John K. “Bayesian Estimation Supersedes the t Test.” (Kruschke 2013)
• Michael Freeman, Visual explanation of hierarchical modeling
• More to come!

Other books

We don’t have time to cover these this semester, but these are all really great and useful resources!

• John K. Kruschke, Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan (Kruschke 2015)

  • Website
  • A. Solomon Kurz, Doing Bayesian Data Analysis in brms and the tidyverse, translation to brms (Kurz 2022)

• Ben Lambert, A Student’s Guide to Bayesian Statistics (Lambert 2018)

• Andrew Gelman, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Donald Rubin, Bayesian Data Analysis (Gelman et al. 2013)

• Allen B. Downey, Think Bayes 2 (Downey 2021)

References

Arel-Bundock, Vincent. 2020. Statistical Rethinking 2 with Stan and R. https://vincentarelbundock.github.io/rethinking2/.

Downey, Allen B. 2021. Think Bayes. 2nd ed. Green Tea Press. https://allendowney.github.io/ThinkBayes2/.

Gelman, Andrew, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Donald Rubin. 2013. Bayesian Data Analysis. 3rd ed. Boca Raton, Florida: Chapman and Hall / CRC.

Johnson, Alicia A., Miles Q. Ott, and Mine Dogucu. 2022. Bayes Rules! An Introduction to Applied Bayesian Modeling. Boca Raton, Florida: Chapman and Hall / CRC. https://www.bayesrulesbook.com/.

Kruschke, John K. 2013. “Bayesian Estimation Supersedes the t Test.” Journal of Experimental Psychology 142 (2): 573–603. https://doi.org/10.1037/a0029146.

———. 2015. Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan. 2nd ed. London: Academic Press / Elsevier. https://doi.org/10.1016/c2012-0-00477-2.

Kruschke, John K., and Torrin M. Liddell. 2018. “The Bayesian New Statistics: Hypothesis Testing, Estimation, Meta-Analysis, and Power Analysis from a Bayesian Perspective.” Psychonomic Bulletin & Review 25 (1): 178–206. https://doi.org/10.3758/s13423-016-1221-4.

Kurz, A. Solomon. 2021. Statistical Rethinking with brms, ggplot2, and the tidyverse. 2nd ed. https://bookdown.org/content/4857/.

———. 2022. Doing Bayesian Data Analysis in brms and the tidyverse. https://bookdown.org/content/3686/.

Lambert, Ben. 2018. A Student’s Guide to Bayesian Statistics. Los Angeles, CA: Sage. https://ben-lambert.com/a-students-guide-to-bayesian-statistics/.

McElreath, Richard. 2020. Statistical Rethinking: A Bayesian Course with Examples in R and Stan. 2nd ed. Boca Raton, Florida: Chapman and Hall / CRC. https://xcelab.net/rm/statistical-rethinking/.