course schedule
The (Rmarkdown) source code for these lectures is available at the github repository,
or by replacing the .slides.html suffix with .Rmd in the link below;
the slides are made using reveal.js.
Here are the slides from
Fall 2021/Winter 2022,
Fall 2020/Winter 2021,
Fall 2019/Winter 2020,
and Fall 2018/Winter 2019.
Unlike previous years, this year (2022), there will only be a Fall term.
Fall 2022
- Week 1 (9/27)
-
Overview of data science - description and estimation, uncertainty and simulation, hypothesis testing.
- Slides: Introduction
- how to git the slide source
- Reading: Quinn & Keough chapters 1-4
- Slides: Hypothesis testing and p-values
- Slides: The t distribution
- Slides: Confidence intervals
- Homework 1 (due 10/6)
- Week 2 (10/4)
-
Visualization, confidence intervals, permutation tests, and the bootstrap.
- Slides: Visualization
- Slides: The bootstrap
- Slides: Permutation tests
- Reading: Quinn & Keough chapters 1-4 (still)
- Homework 2 (due 10/13)
- Week 3 (10/11)
-
Linear models, ANOVA, and formulas.
- Slides: The central limit theorem
- Slides: Linear models
- Slides: Multivariate ANOVA
- Slides: Formulas
- Homework 3 (due 10/20)
- Reading: Quinn & Keough chapter 5, 6, 8
- Week 4 (10/18)
-
Multiple testing, error rates, and some history.
- Slides: Multiple testing
- Slides: Statistics and eugenics
- Slides: A note on P-value thresholds
- Homework 4 (due 10/27)
- Reading: Quinn & Keough chapter 7
- Week 5 (10/25)
-
Random effects and mixed models; intro to Bayesian stats.
- Reading: Quinn & Keough chapter 13
- Reading: Kruschke, chapters 1, 2
- Slides: Random effects
- Slides: Probability rules
- Slides: Prior distributions
- Slides: The Beta distribution
- Slides: Maximum posterior example
- Homework 5 (due 11/3)
- Week 6 (11/1)
-
Bayesian model fitting, Markov chain Monte Carlo
- Reading: Kruschke, chapters 4, 5, 6, 7
- Slides: Posterior sampling with MCMC
- Slides: Baseball: Hierarchical logistic models
- Homework 6 (due 11/15)
- Week 7 (11/8)
-
Logistic models and GLMs; sharing power
- Slides: Intro to brms
- Slides: Generalized Linear Models
- Reading: Quinn & Keough chapter 13
- Reading: Kruschke, chapters 9, 10
- Homework 7 (due 11/21)
- Week 8 (11/15)
-
Robust linear models; data analysis example
- Reading: Donihue, C.M., Herrel, A., Fabre, AC. et al. Hurricane-induced selection on the morphology of an island lizard.
- Slides: Cauchy distribution
- Slides: Robust models
- slides: Hurricane Lizards
- Week 9 (11/22, no class Thursday)
-
Factor analysis, dimensionality reduction, and PCA
- Reading: Quinn & Keough chapter 17
- slides: Dimension reduction and PCA
- slides: On ordination
- Homework 8 (due 12/6)
- Week 10 (11/30)
-
Factor analysis continued, t-SNE; random forests
- Reading: The two cultures, by Leo Breiman
- slides: t-SNE
- slides: Random forests
- Homework 9 and Homework 10 (one of these due 12/8)