TILA311 Generalized Linear Models 1 (2–5 cr)
The course introduces linear statistical modelling through examples from several different fields of application. The course introduces generalized linear models (GLMs) in situations where the response is continuous (ordinary linear regression), dichotomous (logistic regression) or count data (Poisson regression). The course focuses on understanding these methods through simple applications. Instead of traditional lectures, the course practices the use of methods in modelling, calculations and graphics through R-exercises.
After successful completion of the course, the student can
- define the models presented in the course with their assumptions
- choose a model suitable for empirical data and justify the choice
- fit the model with R software
- draw interpret the results and assess the suitability of the fitted model
- write a report on the statistical analysis made.
The course is 5 ECTS credits for students studying a degree in statistics and for students studying intermediate studies in statistics.
Students taking basic studies can either complete the entire course (5 credits) or do only linear regression model part of the course (2 credits).
Please note that the 5 ECTS course gives students of other fields good preparation to complete the courses: Survival Analysis (TILS210) and Mixed Models and Analysis of Longitudinal Data (TILS2300).
Description of prerequisites
The students studying a degree in statistics: Data and measurement, From data to model, R course
For other students: From data to model or Statistical methods basic course or similar information, basic skills of using the R software.