Statistical Inference at WIS
About the course
Welcome to Statistical Inference, an two-week summer course to train biologists in data science and statistical inference. The course runs August 24–September 4, 2025. This webpage has all of the materials for the course.
Personnel
- Course instructor: Justin Bois is a teaching professor in the Division of Biology and Biological Engineering at Caltech, where he teaches a variety of courses, including courses on data analysis in the biological sciences.
- Teaching assistant: Niv Cohen is a Ph.D. student in the Systems Immunology Department at Weizmann.
- Teaching assistant: Hamish Pike is a postdoc in the Systems Immunology Department at Weizmann.
Course structure and schedule
We meet every day, Sunday through Thursday, 9:00–13:00, in the Drory Auditorium in the Weissman Building for a total of ten days. Each day is split into an instructional and practical section. In the instructional section, topics are introduced and discussion in a lecture and/or follow-along format. In the practical sections, students apply the concepts in exercises. The topics of the sessions are below.
- Data practicalities
- Sun, August 24: What are we doing?
- Sun, August 24: Polars and split-apply-combine
- Sun, August 24: Data display
- Theory
- Mon, August 25: Probability review
- Mon, August 25: Sampling out of probability distributions
- Tue, August 26: Sampling with Markov chain Monte Carlo
- Wed, August 27: Bayesian modeling and inference (with prior predictive checks)
- Techniques
- Wed, August 27: Statistical inference by Markov chain Monte Carlo
- Thu, August 31: Mixture models
- Thu, August 28: Model assessment and principled workflows
- Sun, August 31: Summarizing posteriors with optimization
- Specific models
- Mon, September 1: Variate-covariate models
- Tue, September 2: Hierarchical models
- Wed, September 3: Principal component analysis
- Wed, September 3: Probabilistic PCA and factor analysis
- Thu, September 4: Hidden Markov models
- Thu, September 4: Generalized linear models
Copyright and License
Copyright 2025, Justin Bois.
With the exception of pasted graphics, where the source is noted, this work is licensed under a Creative Commons Attribution License CC BY-NC-SA 4.0. All code contained herein is licensed under an MIT license.