Data Analysis for Psychology in R-2
2026/27
Course description
Data Analysis for Psychology in R 2 (DAPR2) is a course taken by second-year students in Psychology. It introduces you to linear modelling using the R programming language.
| Week | Slides | Lab |
|---|---|---|
| Sem 1 Week 1 (01) | Introduction to linear regression | 01: Simple linear regression |
| Sem 1 Week 2 (02) | Interpreting linear models | 02: Multiple regression |
| Sem 1 Week 3 (03) | Testing predictors and evaluating linear models | 03: Significance tests |
| Sem 1 Week 4 (04) | F-tests and model comparison | 04: Model comparison |
| Sem 1 Week 5 (05) | Practice analysis: Linear models (Study brief) | 05: Practice write-up |
| Sem 1 Week 6 | No Lecture | No Lab |
| Sem 1 Week 7 (06) | Categorical predictors and treatment coding | 06: Treatment coding |
| Sem 1 Week 8 (07) | Sum coding | 07: Sum coding |
| Sem 1 Week 9 (08) | Assumptions and diagnostics | 08: Assumptions and diagnostics |
| Sem 1 Week 10 (09) | Bootstrapping and confidence intervals | 09: Bootstrapping |
| Sem 1 Week 11 (10) | Practice analysis: Categorical predictors (Study brief) | 10: Practice write-up |
| --- | ||
| Sem 2 Week 1 (11) | Mean-centering and numeric/categorical interactions | 11: Numeric/categorical interactions |
| Sem 2 Week 2 (12) | Numeric/numeric interactions | 12: Numeric/numeric interactions |
| Sem 2 Week 3 (13) | Categorical/categorical interactions | 13: Categorical/categorical interactions |
| Sem 2 Week 4 (14) | Testing simple effects and correcting for multiple comparisons | 14: Testing simple effects |
| Sem 2 Week 5 (15) | Practice analysis: Interactions (Study brief) | 15: Practice write-up |
| Flexible Learning Week | No Lecture | No Lab |
| Sem 2 Week 6 (16) | Probabilities and log-odds | 16: Probabilities and log-odds |
| Sem 2 Week 7 (17) | Modelling binary outcomes with logistic regression | 17: Logistic regression with one predictor |
| Sem 2 Week 8 (18) | Interactions, assumptions, diagnostics, comparisons | 18: Logistic regression with multiple predictors |
| Sem 2 Week 9 (19) | Practice analysis: Logistic regression (Study brief) | 19: Practice write-up |
| Sem 2 Week 10 (20) | Report feedback [Access via Learn] Exam prep |
Mock Exam [Access via Learn] |