| Week | General & exams | Lectures | Tutorials | Computer tutorials |
| 1 |
General information
|
Lecture 1A: Data
Lecture 1B: Summarizing data
Lecture 2A: Basic probability
Lecture 2B: Probability distributions
|
Tutorial 1 |
Computer tutorial 1: Basics of R/RStudio |
| 2 |
Lecture 3A: Sampling, the CLT, and the standard error
Lecture 3B: μ: estimates, confidence intervals and tests
Lecture 4A: Hypotheses: logic and framework
Lecture 4B: μ: the one-sample t-test and software
|
Tutorial 2 |
Computer tutorial 2: Graphs and simple tests with R |
|
| 3 |
Digital exam
|
Lecture 5A: σ2: estimates, confidence intervals and tests
Lecture 5B: Median: non-parametric tests
Lecture 6A: Two μs or medians: comparisons
Lecture 6B: Two σ2s: comparisons
|
Tutorial 3 |
|
| 4 |
Lecture 7A: Several μs: comparison
Lecture 7B: Several μs and medians: more issues
Lecture 8A: Simple regression analysis
Lecture 8B: Multiple regression analysis and other issues
|
Tutorial 4 |
Computer tutorial 3: Advanced tests with R |
|
| 5 |
Lecture 9A: π: estimates, confidence intervals and tests
Lecture 9B: Contingency tables: tests
Lecture 10A: Two πs: comparison
Lecture 10B: ρ: estimates and tests
|
Tutorial 5 |
Computer tutorial 4: More tests with R, Excel for stats |
|
| 6 |
Digital exam
|
Lecture 11A: Power and design
Lecture 11B: Regression vs. ANOVA
Lecture 12A: Choosing the right test Lecture 12B: Miscellaneous topics |
Tutorial 6 |
|
| ≥7 |
Written exam
Retake digital exam
|
Annotated five-steps procedure Video clips explaining the formula sheet Response class week 7 |