Lecture Plan & Calendar
This calendar keeps the conceptual flow intact (frequency → tables → confounding → causality → regression → design → bias/validity → integration).
Semester plan (starting Week 3)
One lecture per week, with one practical R session and two continuous assessment points.
| Teaching Week | Topic / Lecture | Student Work (Deliverable) | Assessment / Milestone |
|---|---|---|---|
| Week 3 | Lecture 01: Measures of Disease Frequency & Association | Reading + worked examples (2×2 table) | — |
| Week 4 | Lecture 02: Categorical Data Analysis & Contingency Tables | Problem set: chi-square / Fisher basics | — |
| Week 5 | Lecture 03: Confounding & Effect Modification | Stratification interpretation drills | Assignment 1 released |
| Week 6 | Lecture 03b: Practical Dataset in R | Dataset intro + cleaning + simple summaries | Assignment 1 due end-week |
| Week 7 | Lecture 04: Causal Inference in Epidemiology | DAG thinking + causal questions | — |
| Week 8 | Lecture 05: Advanced Confounding Control Measures | Matching / stratification logic + design cautions | CAT 1 (mid-semester) |
| Week 9 | Lecture 06: Logistic Regression in Epidemiology | Output interpretation + OR vs RR reminders | — |
| Week 10 | Lecture 07: Study Designs – Strengths, Biases & Causal Utility | Design-choice vignettes + bias spotting | Assignment 2 released |
| Week 11 | Lecture 08: Bias, Validity, and Modern Methods (Part I) | Bias taxonomy + validity threats | — |
| Week 12 | Lecture 09: Bias, Validity, and Modern Methods (Part II) | Prediction vs causal models + ML cautions | Assignment 2 due end-week |
| Week 13 | Lecture 10: Integrating Methods In Public Health Practice | Evidence interpretation + exam revision guide | — |