Bayesian Inference
Definition: A method of statistical inference based upon Bayes’ theorem, which makes use of epistemological (un)certainty using the mathematical language of probability. Bayesian inference is based on allocating (and reallocating, based on newly-observed data or evidence) credibility across possibilities. Two existing approaches to Bayesian inference include “Bayes factors” (BF) and Bayesian parameter estimation.
Related terms: Bayes Factor, Bayesian statistics, Bayesian Parameter Estimation
References:
- Dienes, Z. (2011). Bayesian versus orthodox statistics: Which side are you on? Perspectives on Psychological Science, 6(3), 274–290. https://doi.org/10.1177/1745691611406920
- Dienes, Z. (2014). Using Bayes to get the most out of non-significant results. Frontiers in Psychology, 5, 781. https://doi.org/10.3389/fpsyg.2014.00781
- Dienes, Z. (2016). How Bayes factors change scientific practice. Journal of Mathematical Psychology, 72, 78–89. https://doi.org/10.1016/j.jmp.2015.10.003
- Etz, A., Gronau, Q. F., Dablander, F., & others. (2018). How to become a Bayesian in eight easy steps: An annotated reading list. Psychonomic Bulletin & Review, 25, 219–234. https://doi.org/10.3758/s13423-017-1317-5
- Kruschke, J. K. (2015). Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan (2nd ed.). Academic Press.
- McElreath, R. (2020). Statistical rethinking: A Bayesian course with examples in R and Stan (2nd ed.). Taylor.
- Wagenmakers, E.-J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Love, J., Selker, R., Gronau, Q. F., Šmíra, M., Epskamp, S., Matzke, D., Rouder, J. N., & Morey, R. D. (2018). Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications. Psychonomic Bulletin & Review, 25(1), 35–57. https://doi.org/10.3758/s13423-017-1343-3
Originally drafted by: Charlotte R. Pennington
Reviewed by: Alaa AlDoh, Bradley Baker, Robert Ross, Markus Weinmann, Tobias Wingen, Steven Verheyen