## Fall 2017: STAT 215A Statistical Models, Theory and Applications

A graudate course in applied statistics taught by Bin Yu. The course covers a wide range of topics that focus on critical thinking for using statistics in the wild. I taught a section each week where I either re-inforced content the students were learning in class, or ran tutorials in a variety of topics in R.

The materials that I prepared can be found in the following github repository: https://github.com/rlbarter/STAT-215A-Fall-2017.

## Spring 2015: STAT 135 Concepts in Statistics

An undergraduate course focusing on common methods in statistics such as MLE, the bootstrap, hypothesis testing and linear models. The instructor for this course was Joan Bruna. I taught a section each week on a topic related to what the students were learning in class.

Lab 2: Confidence intervals, MLE and the delta method (pdf)

Lab 3: Asymptotic MLE and the method of moments (pdf)

Lab 4: Recap, efficiency, sufficiency, bias-variance trade-off (Rao-Blackwell), Bayesian inference (pdf)

Lab 5: Bootstrapping and hypothesis testing (pdf)

Lab 6: Duality of hypothesis testing and confidence intervals, GLRT, Pearson Chi-squared tests and Q-Q plots (pdf)

Lab 7: Distributions derived from the normal distribution, and comparing independent samples (pdf)

Lab 8: Hypothesis testing review, Mann-Whitney test by normal approximation, and Wilcoxon signed rank test (pdf)

Lab 9: Multiple testing, one-way ANOVA and Kruskal-Wallis (pdf)

Lab 10: Two-way ANOVA, randomized block design and Friedmanâ€™s test (pdf)

Lab 11: Tests for categorical data (Fisherâ€™s exact test, Chi-squared tests for homogeneity and independence) and linear regression (pdf)

Lab 12: Multiple linear regression (matrix form), residual analysis and inference for OLS (pdf)

Lab 13: Linear regression, multivariate random variables, prediction, logistic regression and the delta-method (pdf)

Review: Hypothesis testing flow chart (pdf)