This course extends the first part of the R course with some more current methods such as Linear Mixed Effects Models, Generalized Mixed Effects Models, Structural Equation Models and Non-Linear Least Squares Models.
As this course is Part 2, it is required to have basic knowledge in R, and how to perform linear least squares models, Generalized Linear Models, and creating graphs in R (Part 1 of the course or similar knowledge).
The course consists of lectures, hands-on training in programming, statistical computation and homework.
Five days presence in the course and homework to prepare the presentation are required. Furthermore, active participation in the exercises, carrying out an individual statistics project and presentation of the results are expected for the successful completion of the course.