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resources.Rmd
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resources.Rmd
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---
title: "Resources"
description: |
Publications, Resources, and Tools for Undergraduate Bayesian Education
output:
distill::distill_article:
toc: true
toc_depth: 2
---
## Textbooks
- [A First Course in Bayesian Statistical Methods](https://pdhoff.github.io/book/){target="_blank"}
- [An Introduction to Bayesian Thinking: A Companion to the Statistics with R course](https://statswithr.github.io/book/){target="_blank"}
- [Bayes Rules! An Introduction to Bayesian Modeling with R](https://www.bayesrulesbook.com/){target="_blank"}
- [Bayesian Data Analysis](http://www.stat.columbia.edu/~gelman/book/){target="_blank"}
- [Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan](https://jkkweb.sitehost.iu.edu/DoingBayesianDataAnalysis/){target="_blank"}
- [Probability and Bayesian Modeling](https://bayesball.github.io/BOOK/probability-a-measurement-of-uncertainty.html){target="_blank"}
- [Statistical Rethinking: A Bayesian Course with Examples in R and Stan](https://xcelab.net/rm/statistical-rethinking/){target="_blank"}
## Courses
- Carleton College by [Adam Loy](https://github.com/aloy/math315-fall2019){target="_blank"}
- Duke University by [Alexander Volfovsky](https://www2.stat.duke.edu/courses/Fall18/sta601.001//){target="_blank"}
- Smith College by [Miles Ott](https://www.dropbox.com/s/bj91cfk4tkfjwmy/SDS%20390%20Bayes%20Fall%202020%20Syllabus.pdf?dl=0)
- University of California Irvine by [Mine Dogucu](https:stats115.com){target="_blank"}
- Vassar College by [Jingchen Monika Hu](https://github.com/monika76five/Undergrad-Bayesian-Statistics){target="_blank"}
## Papers
- [Albert, J., & Hu, J. (2020). Bayesian Computing in the Statistics and Data Science Curriculum. arXiv preprint arXiv:2002.09716.](https://arxiv.org/abs/2002.09716){target="_blank"}
- [Bolstad, W. M. (2002). Teaching Bayesian statistics to undergraduates: Who, what, where, when, why, and how. In Proceedings of the Sixth International Conference on Teaching of Statistics.](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.215.6479&rep=rep1&type=pdf){target="_blank"}
- [Hoegh, A (2020). Why Bayesian ideas should be introduced in the
Statistics curricula and how to do so. Journal of Statistics Education](https://amstat.tandfonline.com/doi/pdf/10.1080/10691898.2020.1841591){target="_blank"}
- [Hu, J. (2019). A Bayesian Statistics Course for Undergraduates: Bayesian Thinking, Computing and Research. arXiv preprint arXiv:1910.05818.](https://arxiv.org/abs/1910.05818){target="_blank"}
- [Johnson, A., Rundel, C., Hu, J., Ross, K., & Rossman, A. (2020). Teaching an Undergraduate Course in Bayesian Statistics: A Panel Discussion. Journal of Statistics Education, 28(3), 251-261.](https://amstat.tandfonline.com/doi/pdf/10.1080/10691898.2020.1845499){target="_blank"}
- [Page, R., & Satake, E. (2017). Beyond P Values and Hypothesis Testing: Using the Minimum Bayes Factor to Teach Statistical Inference in Undergraduate Introductory Statistics Courses. Journal of Education and Learning, 6(4), 254-266.](https://eric.ed.gov/?id=EJ1150444){target="_blank"}
- [Sarafoglou, A., van der Heijden, A., Draws, T., Cornelisse, J., Wagenmakers, E. J., & Marsman, M. (2018). Combine Statistical Thinking With Scientific Practice: A Protocol of a Bayesian Thesis Project For Undergraduate Students. arXiv preprint arXiv:1810.07496.](https://arxiv.org/abs/1810.07496){target="_blank"}
- [Stewart, S., & Stewart, W. (2014). Teaching Bayesian statistics to undergraduate students through debates. Innovations in Education and Teaching International, 51(6), 653-663.](https://www.tandfonline.com/doi/full/10.1080/14703297.2013.791553?mobileUi=0){target="_blank"}
- [Stewart, W., & Stewart, S. (2014). Teaching Markov Chain Monte Carlo: Revealing the Basic Ideas Behind the Algorithm. PRIMUS, 24(1), 25-45.](https://www.tandfonline.com/doi/full/10.1080/10511970.2013.824054){target="_blank"}
- [van Doorn, J., Matzke, D., & Wagenmakers, E. J. (2020). An in-class demonstration of Bayesian inference. Psychology Learning & Teaching, 19(1), 36-45.](https://journals.sagepub.com/doi/full/10.1177/1475725719848574){target="_blank"}
- [Witmer, J. (2017). Bayes and MCMC for undergraduates. The American Statistician, 71(3), 259-264.](https://www.tandfonline.com/doi/full/10.1080/00031305.2017.1305289){target="_blank"}
## Other Resources
- [`bayesrules`](https://github.com/mdogucu/bayesrules){target="_blank"} R package to supplement learning with Bayes Rules! book.
- [How Data Nerds Found A 131-Year-Old Sunken Treasure](https://fivethirtyeight.com/features/how-data-nerds-found-a-131-year-old-sunken-treasure/){target="_blank"} is a video by FiveThirtyEight that explains how SS Central America was found using Bayesian methods.
- [The Learning Bayesian Statistics Podcast](https://www.learnbayesstats.com/){target="_blank"}
## Editing the List
If you would like to make suggestions to this list, please do so either by creating an issue or a pull request on the [GitHub repo](https://www.github.com/mdogucu/undergrad-bayes){target="_blank"} (prefered) or via email. Please note that this list specifically focuses on _undergraduate_ Bayesian education. If you are making suggestions of a resource, please note how it is appropriate at the _undergraduate level_ if it is not obvious from the title or abstract.