Universität Wien

040195 KU Data Analysis on Organization and Personell (MA) (2018W)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Thursday 04.10. 09:45 - 13:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 11.10. 09:45 - 13:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 18.10. 09:45 - 13:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 08.11. 09:45 - 13:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 22.11. 09:45 - 13:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 29.11. 09:45 - 15:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 29.11. 15:00 - 16:45 Seminarraum 14 Oskar-Morgenstern-Platz 1 2.Stock

Information

Aims, contents and method of the course

This course introduces students to regression tools for analyzing data in management, economics, finance and related disciplines. Extensions include regression with discrete random variables, instrumental variables regression, quasi-experiments, and regression with time series data. The objective of the course is for the student to learn how to conduct – and how to critique – empirical studies in management, economics, finance and related fields. Accordingly, the emphasis of the course is on empirical applications. The mathematics of econometrics will be introduced only as needed and will not be a central focus. Upon completion of the course, students will be able to undertake regression analysis and inference on a variety of hypotheses involving cross-sectional and time series data.

Assessment and permitted materials

Your final grade is determined by your performance on the quizzes, assignments, final essay, class attendance and participation. Grades will be reduced for absence.
Exams consist of essay type questions. Make-up exams will not be given unless the student has a medical or other serious reason.
Students should hand in homework assignments before class on the day they are due. Assignments will be distributed in class or on line. each student must write up his or her answers separately.
Following content will be covered in class,
-Introduction to Stata, Descriptive Statistics
-Correlation, T-test, Hypothesis Testing
-Univariate OLS Regression
-Multivariate OLS Regression, Dummy variable
-Logit Model

Your final grade is determined by your performance on the in class participation, assignments and presentation.
Make-up exams will not be given unless the student has a medical or other serious reason.
Students should hand in homework assignments before class on the day they are due. Assignments will be distributed in class or on line. each student must write up his or her answers separately.

Passing grades can generally not be earned by students who miss more than 10% of the total class-time.
Exam review is possible during regular semester time by appointment.

Minimum requirements and assessment criteria

Basic knowledge of Business Mathematics and Statistics are required.

Examination topics

assignments, final presentation, class attendance and participation.

Reading list

Wooldridge „Introductory Econometrics“
– Chapters 1-8, 15, 17
Technical Jargon and lengthy, but a classic
Peter Kennedy „A guide to Econometrics“
– Chapters 1-12, 16, 17
More of a critique but some find it more readable then Wooldridge
Kohler/Kreuter „Data Analysis using Stata“
Very much on descriptives and data management, less on regressions. Chapter 8 and 9 mostly relev
Baum „An Introduction to Modern Econometrics using Stata“
Requires some background in stata, but covers more details. Chapters 4, 8 and 9 mostly relevant

Association in the course directory

Last modified: Mo 07.09.2020 15:28