FOR-009 Statistical modeling with R software (5 op)
- Period 4, the course is lectured at least every two years.
- Preceding studies: Basics of linear regression analysis.
After completing the course, the student is able to do statistical modelling with the R software. The student is able to perform the statistical modelling by using generalized linear models and generalized linear mixed models. After completing the course, the student has ability to perform multilevel hierarchical modelling with R software.
R software, linear models, linear mixed models, Beta and Gamma regression, Poisson log-linear models, logistic regression analysis, generalized linear mixed models.
Lecture notes and R manuals are made available at the Moodle learning environment.
Faraway (2006). Extending the linear model with R: generalized linear, mixed effects, and nonparametric regression models. Chapman & Hall.
Agresti (2015). Foundations of linear and generalized linear models. John Wiley & Sons.
The course is completed by following the online education. The course includes weekly assignments and the final exam at the end of the course.
21 hours online lectures, 9 hours assignments, and 105 hours self-studying.
Evaluation on scale 0-5. Rating is based on the exam (80%) and the weekly assignments (20%).
University Lecturer Jarkko Isotalo.
Teaching in English.