Exercise: Probability Revision and Bayes
2022
This sample exercise and solution set supports the teaching pack on Probability Revision and Bayes, in which students are introduced to the implications of imperfect information, acquire a conceptual understanding of Bayes theorem, and gain practical skills in performing probability revision. In addition to the sample exercise, materials include an instructor's note, videos, companion slides, a glossary, an annotated bibliography, and additional support.
Learning Objectives
- Demonstrate a conceptual understanding of Bayes’ theorem and probability revision.
- Differentiate between test characteristics (e.g., probability of positive test given disease presence) and posterior probabilities (e.g., probability of disease given a positive test).
- Perform probability revision using a flow diagram, 2 x 2 table, Bayes’ formula and tree inversion.
The exercise provides just 2-3 simple examples of the types of short questions that can be useful for practicing some of the skills covered in this teaching pack. These should be modified, tailored, and expanded upon to meet the goals of specific classes.
This teaching pack was developed by Sue J. Goldie at the Center for Health Decision Science, Harvard T.H. Chan School of Public Health. The multimedia components were developed as part of a series of pilots in the CHDS Media Hub, led by Jake Waxman, where media-based pedagogy experiments contribute to new ways of thinking about short form content.
Related Files:
Source:
Exercise. Teaching Pack: Probability Revision and Bayes. Center for Health Decision Science, Harvard T.H. Chan School of Public Health 2022. https://repository.chds.hsph.harvard.edu/repository/2719