STATISTICAL COMPUTING

This GitHub serves as a repository for the statistical computing courses STT 802 and EPI-853b.

Instructors: Hyokyoung Grace Hong (hhong@stt.msu.edu) & Gustavo de los Campos (gustavoc@msu.edu)

Syllabus

Time & Place M/W 3:00 PM - 4:20 PM. E109 Fee Hall.

Modules

Module 1 (Introduction)

1. R Studio/R Markdown
2. Introduction to R
3. Data preparation and descriptive analyses

Module 2 (Statistical Models)

1. Linear regression models (point estimates, SEs, t-test, p-values)
2. Generalized linear models (GLM)
3. Survival models
4. Quantile regression models

Module 3 (High-dimensional Data Analysis)

1. Regularized regression methods
2. Variable screening methods

Module 4 (Maximum Likelihood)

1. Maximization using general purpose optimization algorithms
2. The EM-Algorithm

Module 5 (Monte Carlo Methods)

1. Sampling Random Variables
2. Power Analysis

Module 6 (Resampling methods)

1. Bootstrap (application: SEs for odds ratios in logistic regression)
2. Permutation test (p-values for odds ratios in logistic regression)

Homeworks

1. HW1
2. HW2
3. HW3