course schedule
Here is the schedule for Winter 2019. See below for Fall 2018.
The (Rmarkdown) source code for many of these lectures is available at the github repository,
or by replacing the .slides.html suffix to .Rmd in the link below;
the slides are made using reveal.js.
Winter 2019
- Week 11 (1/7, Peter)
-
Robust multiple linear regression; scale mixtures; model selection with crossvalidation; introduction to Generalized Linear Models (GLM).
- Tuesday & Thursday Slides
- Reading: (Kruschke, ch 15, 16, 17)
- Week 12 (1/14, Peter)
-
More GLMs; Poisson regression; detecting and modeling overdispersion; quantifying goodness-of-fit.
- Tuesday & Thursday Slides
- Reading: (Kruschke, ch 24)
- Homework 2, due 1/24.
- Week 13 (1/21, Peter)
-
Categorical data: chi-square for contingency tables, permutation tests; categorical prediction.
- Tuesday Slides
- Reading: (Kruschke, ch 22, 24)
- Homework 3, due 1/31.
- Week 14 (1/28, Peter)
-
Sparsifying priors and variable selection.
- Tuesday Slides
- Reading: (Kruschke, ch 19, 20)
- Week 15 (2/4, Bill)
-
Linear algebra, latent factor analysis.
- Week 16 (2/11, Bill)
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Factor/PCA/PCoA.
- Week 17 (2/18, Bill)
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Linear discriminant analysis and/or MANOVA.
- Week 18 (2/25, Peter)
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Visualization: clustering, t-SNE, penalized PCA.
- Week 19 (2/32, Peter)
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Spatial statistics and network models.
- Week 20 (2/39, Peter)
-
Time series.
Fall 2018
- Week 1 -
- Week 2 -
- Week 3 -
- Week 4 -
- Week 5 -
- Week 6 -
- Week 7 -
- Week 8 -
-
Bayesian statistics - prior distributions and uncertainty - using Stan)
- Tuesday & Thursday Slides
- in-class demo - Beta-Binomial analysis
- reading: Kruschke, chapters 5 and 6 (and: install and test rstan)
- Week 9 -
-
Bayesian hierarchical modeling - shrinkage, and sharing power
- Tuesday Slides
- reading: Kruschke, chapters 7, 9, and 14
- Week 10 -
-
Logistic regression - simulation, posterior predictive sampling - robust regression
- Tuesday & Thursday Slides
- reading: Kruschke, chapters 16, 17, and 13