Startsida
MAI0137 - Lectures
During the Lectures the theory is presented and examples intended to illustrate the theoretical results are given.| Activity | When and where | Description |
| Lecture 1 | TBD | Statistical models. Exponential family. Inference principles. Principles of data reduction. (LZ: 2 and 3, DB: 1.4-1.5, 3.2-3.3) |
| Lecture 2 | TBD | Estimation. Point estimation (MLE, Method of moment, Least squares, etc). Methods of evaluating estimators. (LZ: 4, DB: 1.6, 4) |
| Lecture 3 | TBD | Hypothesis testing. LRT. Interval estimation. Methods of evaluating tests and interval estimators. (LZ: 5, DB: 5) |
| Lecture 4 | TBD | Asymptotic properties of estimators and tests. (LZ: 4.3) |
| Lecture 5 | TBD | General linear models. Multiple linear regression. (LZ: 6, DB: 6) |
| Lecture 6 | TBD | ANOVA. Single-factor, two-factor and multifactor models. (LZ: 6, DB: 6) |
| Lecture 7 | TBD | Non-parametric methods. |
| Lecture 8 | TBD | Generalized linear models. Logistic regression. Poisson regression. (DB: 7 and 9) |
| Lecture 9 | TBD | Clustered and Longitudinal data. Repeated measures models. Mixed linear models. (DB: 11) |
| Lecture 10 | TBD | Introduction to Bayesian statistical inference. (DB: 12-14) |
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Last updated: 2021-08-13