109.012 Econometrics 1: Linear Models
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2020W, UE, 1.0h, 1.5EC


  • Semester hours: 1.0
  • Credits: 1.5
  • Type: UE Exercise
  • Format: Presence

Learning outcomes

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.


Subject of course

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.

Teaching methods

Exercise sessions with completed problems to be marked in TUWEL.


Mode of examination


Additional information

Wir stellen auf online Modus um. Alle Infos finden Sie bis auf weiteres auf der TUWEL Kursseite.

The exercise sessions start on Tuesday, October 13, 2020.



Course dates

Tue16:00 - 17:0013.10.2020 - 26.01.2021EI 4 Reithoffer HS - ETIT UE 109.012
Econometrics 1: Linear Models - Single appointments
Tue13.10.202016:00 - 17:00EI 4 Reithoffer HS - ETIT UE 109.012
Tue20.10.202016:00 - 17:00EI 4 Reithoffer HS - ETIT UE 109.012
Tue27.10.202016:00 - 17:00EI 4 Reithoffer HS - ETIT UE 109.012
Tue12.01.202116:00 - 17:00EI 4 Reithoffer HS - ETIT UE 109.012
Tue19.01.202116:00 - 17:00EI 4 Reithoffer HS - ETIT UE 109.012
Tue26.01.202116:00 - 17:00EI 4 Reithoffer HS - ETIT UE 109.012

Examination modalities

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).

        grade   >   80.0%   1
            >   70.0%   2
            >   60.0%   3
            >   50.0%   4
           <=   50.0%   5

Course registration

Begin End Deregistration end
27.07.2020 00:00 18.10.2020 23:59 25.10.2020 23:59



No lecture notes are available.

Previous knowledge

Basic knowledge in linear algebra, probability theory and statistics are recommended.

Accompanying courses


  • Attendance Required!