Linear Models (SL_112)
About Study Course
Objective
This course gives students the in-depth knowledge of the theory of linear models and provides training for applying the theory to solve practical problems. The software package R will be used for computation and independently prepared data analysis projects.
Prerequisites
Calculus; Probability.
Learning outcomes
• as a result of completion of a study course, the student is able to demonstrate an in-depth knowledge of the theory behind linear models;
• explain the limitations and assumptions of the linear models;
• discuss the different parameterisation options in linear models.
Is able to independently:
• choose appropriate model for the data and check the model assumptions;
• interpret and use (predictions; inference) the estimated model;
• perform multiple comparisons and post-hoc tests.
The students will be able to:
• solve prediction problems using linear models’ methodology.
• use linear models to answer complex what-if questions (Example: what would the average difference between male and female blood pressure be, if the proportion of overweight population would be the same for both genders?).
• critically assess the linear models used in scientific publications and the validity of the conclusions made by authors.
Study course planning
| Study programme | Study semester | Program level | Study course category | Lecturers | Schedule |
|---|---|---|---|---|---|
| Biostatistics, MFBS | 2 | Master’s | Required | Māris Munkevics | |
| Biostatistics, MFBSeng | 2 | Master’s | Required |
