The Current State of Undergraduate Bayesian Education and Recommendations for the Future

References

• Albert, J. (2009), Bayesian Computation with R (2nd ed.), New York: Springer.
   Google Scholar
• Albert, J., and Hu, J. (2019), Probability and Bayesian Modeling (1st ed.), Boca Raton, FL: Chapman and Hall/CRC.
   Google Scholar
• Albert, J., and Hu, J. (2020), “Bayesian Computing in the Undergraduate Statistics Curriculum,” Journal of Statistics Education, 28, 236–247.
   Web of Science ®Google Scholar
• Andrade, L., and Fernández, F. (2016), “Interpretation of Confidence Interval Facing the Conflict,” Universal Journal of Educational Research, 4, 2687–2700. DOI: 10.13189/ujer.2016.041201.
   Google Scholar
• Barcena, M. J., Garin, M. A., Martin, A., Tusell, F., and Unzueta, A. (2019), “A Web Simulator to Assist in the Teaching of Bayes’ Theorem,” Journal of Statistics Education, 27, 68–78. DOI: 10.1080/10691898.2019.1608875.
   Web of Science ®Google Scholar
• Bolstad, W. M. and Curran, J. M. (2016), Introduction to Bayesian Statistics (3rd ed.), Hoboken, NJ: Wiley.
   Google Scholar
• Bürkner, P.-C. (2017), “brms: An R package for Bayesian Multilevel Models Using Stan,” Journal of Statistical Software, 80, 1–28. DOI: 10.18637/jss.v080.i01.
   PubMed Web of Science ®Google Scholar
• Carlin, B. P., and Louis, T. A. (2008), Bayesian Methods for Data Analysis (3rd ed.), Boca Raton, FL: Chapman and Hall/CRC.
   Google Scholar
• Christensen, R., Johnson, W., Branscum, A., and Hanson, T. E. (2010), Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians (1st ed.), Boca Raton, FL: Chapman and Hall/CRC.
   Google Scholar
• Cobb, G., (2015), “Mere Renovation is too Little too Late: We Need to Rethink our Undergraduate Curriculum from the Ground up,” The American Statistician, 69, 266–282. DOI: 10.1080/00031305.2015.1093029.
   Web of Science ®Google Scholar
• Cowles, M. K. (2013), Applied Bayesian Statistics: With R and OpenBUGS Examples, New York: Springer.
   Google Scholar
• Eadie, G., Huppenkothen, D., Springford, A., and McCormick, T. (2019), “Introducing Bayesian Analysis with m&m’s: An Active-Learning Exercise for Undergraduates,” Journal of Statistics Education, 27, 60–67.
   Web of Science ®Google Scholar
• Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., and Rubin, D. B. (2013), Bayesian Data Analysis (3rd ed.), Boca Raton, FL: Chapman and Hall/CRC.
   Google Scholar
• Goodrich, B., Gabry, J., Ali, I., and Brilleman, S. (2020), “rstanarm: Bayesian Applied Regression Modeling via Stan,” R package version 2.21.1. https://mc-stan.org/rstanarm.
   Google Scholar
• Hoegh, A. (2020), “Why Bayesian Ideas Should be Introduced in the Statistics Curricula and How to do so,” Journal of Statistics Education, 28, 222–228. DOI: 10.1080/10691898.2020.1841591.
   Web of Science ®Google Scholar
• Hoff, P. D. (2009), A First Course in Bayesian Statistical Methods, New York: Springer.
   Google Scholar
• Horton, N. J. (2015), “Challenges and Opportunities for Statistics and Statistical Education: Looking Back, Looking Forward,” The American Statistician, 69, 138–145. DOI: 10.1080/00031305.2015.1032435.
   Web of Science ®Google Scholar
• Horton, N. J., Baumer, B. S., and Wickham, H. (2015),” Setting the Stage for Data Science: Integration of Data Management Skills in Introductory and Second Courses in Statistics,” Chance. DOI: https://chance.amstat.org/2015/04/setting-the-stage.
   Google Scholar
• Hu, J. (2019), “Teaching Upper Level Undergraduate Statistics through a Shared/Hybrid Model,” CHANCE, 32, 31–36. DOI: 10.1080/09332480.2019.1606595.
   Google Scholar
• Hu, J. (2020), “A Bayesian Statistics Course for Undergraduates: Bayesian Thinking, Computing, and Research,” Journal of Statistics Education, 28, 229–235.
   Web of Science ®Google Scholar
• Hu, J., and Dogucu, M. (2022), “Content and Computing Outline of Two Undergraduate Bayesian Courses: Tools, Examples, and Recommendations,” Stat, 11, e452. DOI: 10.1002/sta4.452.
   Web of Science ®Google Scholar
• Johnson, A. A., Ott, M., and Dogucu, M. (2022), Bayes Rules! An Introduction to Applied Bayesian Modeling (1st ed.), Boca Raton, FL: Chapman and Hall/CRC.
   Google Scholar
• Johnson, A., Rundel, C., Hu, J., Ross, K., and Rossman, A. (2020), “Teaching an Undergraduate Course in Bayesian Statistics: A Panel Discussion,” Journal of Statistics Education, 28, 251–261. DOI: 10.1080/10691898.2020.1845499.
   Web of Science ®Google Scholar
• Kruschke, J. (2014), Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan (2nd ed.), Amsterdam: Academic Press.
   Google Scholar
• Lambert, B. (2018), A Student’s Guide to Bayesian Statistics (1st ed.), Thousand Oaks, CA: SAGE Publications Ltd.
   Google Scholar
• McElreath, R. (2020), Statistical Rethinking: A Bayesian Course with Examples in R and Stan (2nd ed.), Boca Raton, FL: Chapman and Hall/CRC.
   Google Scholar
• Nolan, D., and Temple Lang, D. (2010), “Computing in the Statistics Curricula,” The American Statistician, 64, 97–107. DOI: 10.1198/tast.2010.09132.
   Web of Science ®Google Scholar
• Reich, B. J., and Ghosh, S. K. (2019), Bayesian Statistical Methods (1st ed.), Boca Raton, FL: Chapman and Hall/CRC.
   Google Scholar
• Rosenberg, J., Kubsch, M., Wagenmakers, E.-J., and Dogucu, M. (2022), “Making Sense of Uncertainty in the Science Classroom: A Bayesian Approach,” Science & Education. DOI: 10.1007/s11191-022-00341-3..
   Web of Science ®Google Scholar
• Rouder, J. N., and Morey, R. D. (2019), “Teaching Bayes’ Theorem: Strength of Evidence as Predictive Accuracy,” The American Statistician, 73, 186–190. DOI: 10.1080/00031305.2017.1341334.
   Web of Science ®Google Scholar
• Rubin, D. B. (1987), Multiple Imputation for Nonresponse in Surveys, New York: Wiley.
   Google Scholar
• Sivia, D. S., and Skilling, J. (2006), Data Analysis: A Bayesian Tutorial (2nd ed.), Oxford: Oxford University Press.
   Google Scholar
• Sotos, A. E. C., Vanhoof, S., Van den Noortgate, W., and Onghena, P. (2007), “Students’ Nisconceptions of Statistical Inference: A Review of the Empirical Evidence from Research on Statistics Education,” Educational Research Review, 2, 98–113. DOI: 10.1016/j.edurev.2007.04.001.
   Google Scholar
• Stan Development Team (2021), “Stan User’s Guide 2.26.”
   Google Scholar
• U.S. News (2021a), “2021 Best National University Rankings,” Available at https://www.usnews.com/best-colleges/rankings/national-universities. Accessed March 30, 2021.
   Google Scholar
• U.S. News (2021b), “National Liberal Arts Colleges,” available at https://www.usnews.com/best-colleges/rankings/national-liberal-arts-colleges. Accessed March 30, 2021.
   Google Scholar
• Wasserstein, R. L., and Lazar, N. A. (2016), “The ASA Statement on p-values: Context, Process, and Purpose,” The American Statistician, 70, 129–133. DOI: 10.1080/00031305.2016.1154108.
   Web of Science ®Google Scholar
• Witmer, J. (2017), “Bayes and MCMC for Undergraduates,” The American Statistician, 71, 259–264. DOI: 10.1080/00031305.2017.1305289.
   Web of Science ®Google Scholar