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Description
Notebook proposal
Title: Bayesian Power Analysis
Why should this notebook be added to pymc-examples?
As pointed out in #349, we don't have anything currently on hypothesis testing, and nothing (nearly nothing?) on decision making. Filling this gap in the topic coverage would be good.
The notebook could go into a new category of "Hypothesis Testing" or the existing "How to" category.
PS This issue was inspired by the proposal by @cetagostini to bring Bayesian Power Analysis to CasusalPy
Suggested categories:
- Level: Beginner or intermediate
Related notebooks
I don't believe there would be any overlap or redundancy caused by adding this. However the proposed notebook might be grouped in with one on hypothesis testing (see #349) and with currently WIP PR #477 on decision utility functions.
References
Indicative references:
- https://stats.stackexchange.com/questions/65754/is-power-analysis-necessary-in-bayesian-statistics
- https://www.rdatagen.net/post/2021-06-01-bayesian-power-analysis/
- Kruschke, J.K., Liddell, T.M. The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective. Psychon Bull Rev 25, 178–206 (2018). https://doi.org/10.3758/s13423-016-1221-4
- Peter Rosenfeld, J., Olson, J.M. Bayesian Data Analysis: A Fresh Approach to Power Issues and Null Hypothesis Interpretation. Appl Psychophysiol Biofeedback 46, 135–140 (2021). https://doi.org/10.1007/s10484-020-09502-y
- Baker, R., & Hirudayaraj, M. (2019). Power Analysis, p Values, and Bayesian Techniques: How Bayesian Techniques Can Be Used in HRD Literature. Advances in Developing Human Resources, 21(4), 438-465. https://doi.org/10.1177/1523422319870565