UO Advanced Biological Statistics

Course schedule, 2018/2019

Here is the schedule for Fall 2018 and Winter 2019. 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.

Fall 2018

Week 1 -

Introduction to R

Week 2 -

Probability, correlation, standard errors, estimation

Week 3 -

Hypothesis testing, $t$-test, permutation tests, and tidy data

Week 4 -

Data visualization, linear models

Week 5 -

Linear regression

Week 6 -

ANOVA, and git

Week 7 -

Experimental design and factorial ANOVA; mixed models; ANCOVA

Week 8 -

Bayesian statistics - prior distributions and uncertainty - using Stan)

Week 9 -

Bayesian hierarchical modeling - shrinkage, and sharing power

Week 10 -

Logistic regression - simulation, posterior predictive sampling - robust regression

Winter 2019

Week 11 (1/7, Peter)

Robust multiple linear regression; scale mixtures; model selection with crossvalidation; introduction to Generalized Linear Models (GLM).

Week 12 (1/14, Peter)

More GLMs; Poisson regression; detecting and modeling overdispersion; quantifying goodness-of-fit.

Week 13 (1/21, Peter)

Categorical data: chi-square for contingency tables, permutation tests; categorical prediction.

Week 14 (1/28, Peter)

Sparsifying priors and variable selection.

Week 15 (2/4, Bill)

Linear algebra, latent factor analysis, intro to multivariate

Week 16 (2/11, Bill)

Factor/PCA/PCoA/MDS

Week 17 (2/18, Bill)

MANOVA and Discriminant Function Analysis (DFA)

Week 18 (2/25, Peter)

Visualization: nonnegative matrix factorization and constrained PCA

Week 19 (3/4, Peter)

Modeling mixtures of expression data; clustering in Stan (t-SNE)

Week 20 (3/11, Peter)

Introduction to time series and spatial statistics.