APH101-Biostat-and-R-programming-course

A repo for undergrad Y2 course: Biostatistics and R programming

Syllabus

Delivery: Lecture & Lab

1. Introduction to R environment, R functions, R data types; workspace and files, R scripts and packages, R graphics
2. Parametric test 1: t-tests
3. Parametric test 2: one-way analysis of variance
4. Parametric test 3: two-way analysis of variance
5. Non-parametric test 1: rank sum test for <=2 samples
6. Non-parametric test 2: Kruskal-Wallis test, Friedman test
7. Non-parametric test 3: inter-rater reliability for categorical variables, Fisher’s exact test, chi-square test for R×C tables
8. Multiple linear regression
9. Logistic regression
10. Survival analysis 1: survival data and Kaplan Meier test
11. Survival analysis 2: Cox proportional hazards regression models
12. Meta-analysis 1: basic introduction and test for heterogeneity
13. Meta-analysis 2: fixed and random effect models