After successful completion of the course, students are able to derive the basic theory of linear regression models and to apply these methods for concrete data sets, as well as interpreting the corresponding software output and test statistical hypothesis.
This course provides some further insights into the methods presented in the lecture and demonstrates the application of these methods. This problem solving course will include theoretical examples as well as actual application to real world data sets.
Exercise sessions with completed problems to be marked in TUWEL.
The exercise sessions start on Tuesday, October 8, 2019.
Registration in TISS.
Please mark complete problems in TUWEL.
The two exercise sessions with the lowest mark do not count towards the grade, but for the marks to count it is necessary to attend the corresponding exercise session (absolutely no exceptions).
Basic knowledge in linear algebra, probability theory and statistics are recommended.
