105.628 Econometrics for Business Informatics
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2019S, VU, 2.0h, 3.0EC

Properties

  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VU Lecture and Exercise

Aim of course

Familiarity with elementary econometric models and methods (linear regression: least-squares  estimation, Gauss-Markov, prediction, specification and testing) as well as solving applied problems.

Subject of course

Introduction to econometric models and methods. Linear regression and least-squares estimation, selected applied problems.

Additional information

The course language is English. The course consists of a lecture and an excercise part which will roughly alternate weekly. There will be 3 different groups for the exercise part, registration is through TISS. The homework problems for the exercise sessions should be marked in TUWEL. The course starts for all students on Wednesday, March 6 at 2.00pm in FH 8 Nöbauer HS with the lecture section. For further information, please see the course syllabus (under "Documents").

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Wed14:00 - 16:0006.03.2019 - 26.06.2019FH 8 Nöbauer HS - MATH Econometrics for Business Informatics
Wed14:00 - 16:0013.03.2019 - 26.06.2019Sem.R. DB gelb 03 Econometrics for Business Informatics
Wed14:00 - 16:0013.03.2019 - 26.06.2019Sem.R. DA grün 05 Econometrics for Business Informatics
Wed14:00 - 18:0003.07.2019Sem.R. DA grün 05 105.628 VU Econometrics for Business Informatics retake exams
Econometrics for Business Informatics - Single appointments
DayDateTimeLocationDescription
Wed06.03.201914:00 - 16:00FH 8 Nöbauer HS - MATH Econometrics for Business Informatics
Wed13.03.201914:00 - 16:00FH 8 Nöbauer HS - MATH Econometrics for Business Informatics
Wed13.03.201914:00 - 16:00Sem.R. DA grün 05 Econometrics for Business Informatics
Wed13.03.201914:00 - 16:00Sem.R. DB gelb 03 Econometrics for Business Informatics
Wed20.03.201914:00 - 16:00FH 8 Nöbauer HS - MATH Econometrics for Business Informatics
Wed20.03.201914:00 - 16:00Sem.R. DA grün 05 Econometrics for Business Informatics
Wed20.03.201914:00 - 16:00Sem.R. DB gelb 03 Econometrics for Business Informatics
Wed27.03.201914:00 - 16:00FH 8 Nöbauer HS - MATH Econometrics for Business Informatics
Wed27.03.201914:00 - 16:00Sem.R. DA grün 05 Econometrics for Business Informatics
Wed27.03.201914:00 - 16:00Sem.R. DB gelb 03 Econometrics for Business Informatics
Wed03.04.201914:00 - 16:00FH 8 Nöbauer HS - MATH Econometrics for Business Informatics
Wed03.04.201914:00 - 16:00Sem.R. DA grün 05 Econometrics for Business Informatics
Wed03.04.201914:00 - 16:00Sem.R. DB gelb 03 Econometrics for Business Informatics
Wed10.04.201914:00 - 16:00FH 8 Nöbauer HS - MATH Econometrics for Business Informatics
Wed10.04.201914:00 - 16:00Sem.R. DA grün 05 Econometrics for Business Informatics
Wed10.04.201914:00 - 16:00Sem.R. DB gelb 03 Econometrics for Business Informatics
Wed08.05.201914:00 - 16:00FH 8 Nöbauer HS - MATH Econometrics for Business Informatics
Wed08.05.201914:00 - 16:00Sem.R. DA grün 05 Econometrics for Business Informatics
Wed08.05.201914:00 - 16:00Sem.R. DB gelb 03 Econometrics for Business Informatics
Wed15.05.201914:00 - 16:00FH 8 Nöbauer HS - MATH Econometrics for Business Informatics

Examination modalities

written and oral

Final grade: exercises, 2 written exams.

Course registration

Use Group Registration to register.

Group Registration

GroupRegistration FromTo
Exercise Section Group 131.01.2019 17:0010.03.2019 23:59
Exercise Section Group 231.01.2019 17:0010.03.2019 23:59
Exercise Section Group 331.01.2019 17:0010.03.2019 23:59

Curricula

Study CodeObligationSemesterPrecon.Info
066 926 Business Informatics Mandatory

Literature

  • Wooldridge (2013) Introductory Econometric: A Modern Approach.
  • Ruud (2000) An Introduction to Classical Econometric Theory.
  • Verbeek (2012) A Guide to Modern Econometrics.
  • Greene (2011) Econometric Analysis.
  • Kleiber & Zeileis (2008) Applied Econometrics in R.

Previous knowledge

Mathematics and statistics at bachelor level.

Language

English