| Week | Lecture | PCLab | Date |
|---|---|---|---|
| 1 | Dies academicus | Introduction to R | 18 Oct 2023 |
| 2 | Introductions | Data manipulation and import/export with R | 25 Oct 2023 |
| 3 | Mathematical preliminaries | Visualization and data manipulation with R | 01 Nov 2023 |
| 4 | The linear model | Linear regression | 08 Nov 2023 |
| 5 | Categorical variables (ANOVA) and dummy coding | Hypothesis testing and ANOVA | 15 Nov 2023 |
| 6 | Multiple linear regression | Multiple linear regression | 22 Nov 2023 |
| 7 | Maximum Likelihood and outlook to Bayesian statistics | Introduction to Bayesian inference | 29 Nov 2023 |
| 8 | Generalized linear models I | Generalized linear models I | 06 Dec 2023 |
| 9 | Generalized linear models II | Generalized linear models II | 13 Dec 2023 |
| 10 | Multivariate methods I | Raster Data in R | 20 Dec 2023 |
| Principal component analysis | 20 Dec 2023 | ||
| 11 | Multivariate methods II | Discriminant function analysis and Model validation | 10 Jan 2024 |
| 12 | Understanding spatial data | Spatial vectors in R | 17 Jan 2024 |
| 13 | Point pattern analysis | Point pattern analysis in R | 24 Jan 2024 |
| 14 | Spatial autocorrelation and interpolation | Semivariogram analysis and kriging | 31 Jan 2024 |
| 15 | Spatial weights and linear modeling | Spatial regression models | 07 Feb 2024 |
| 16 | No class | No class | 14 Feb 2024 |
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