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| Detailed information |
| Pre-requisites |
(*)keine
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| Original study plan |
Bachelor's programme Statistics and Data Science 2025W |
| Learning Outcomes |
Competences |
| Students know the basic methods and be able to apply the concepts of classical linear regression, ANOVA and ANCOVA and general linear regression
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| Skills |
Knowledge |
- Knowing and understanding concept of linear models and their model assumptions (k1, k2).
- Applying and interpreting different linear models (k3, k4, k5).
- Applying the methods of linear models with the freeware R (k3)
- Understanding and applying model fitting, testing different models (k2, k3, k4).
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- Simple linear regression: Model assumptions, confidence intervals and hypothesis tests of parameters, residual diagnostics
- Multiple regression: Modelling of effects, confidence regions, F-tests, model fit, testing models,
- ANOVA
- ANCOVA
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| Criteria for evaluation |
homework and written exam
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| Methods |
presentation by the lecturer
presentation of homework examples by students
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| Language |
German |
| Study material |
Fahrmeir L., Kneib T. , Lang S. and Marx B., Regression: Models, Methods and Applications, Springer, 2013
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| Changing subject? |
No |
| Corresponding lecture |
(*)4MSOMKV: KV Ökonometrische Modelle (Statistik) (4 ECTS)
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