Universität Wien
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040217 KU Data Analysis on Organization and Personell (MA) (2022S)

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

service email address: opim.bda@univie.ac.at
Moodle

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. 25 participants
Language: English

Lecturers

Classes

MI 02.03.2022 11.30-14.45 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß (Bestätigt)
MI 09.03.2022 11.30-14.45 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß (Bestätigt)
MI 23.03.2022 11.30-14.45 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß (Bestätigt)
MI 30.03.2022 11.30-14.45 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß (Bestätigt)
MI 06.04.2022 09.45-11.15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß (Bestätigt)
MI 06.04.2022 11.30-14.45 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß (Bestätigt)
MI 06.04.2022 15.00-16.30 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß (Bestätigt)
MI 06.04.2022 16.45-20.00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß (Bestätigt)
DO 07.04.2022 09.45-11.15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock (Bestätigt)
DO 07.04.2022 11.30-13.00 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock (Bestätigt)
DO 07.04.2022 13.15-14.45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock (Bestätigt)
DO 07.04.2022 15.00-16.30 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock (Bestätigt)
DO 07.04.2022 16.45-18.15 Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock (Bestätigt)

Information

Aims, contents and method of the course

Summary: “This course emphasizes statistical methods for analyzing data used by social scientists. Topics include simple and multiple regression analyses and the various methods of detecting and correcting data problems.”
Goal: 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.
This course introduces students to regression tools for analyzing data in 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 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.

Assessment and permitted materials

Your final grade is determined by your performance on the quizzes, assignments, presentations and class participation.
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.
Exam review is possible during regular semester time by appointment.

Minimum requirements and assessment criteria

Basic knowledge of Business Mathematics and Statistics are required.
Your final grade is determined by your performance on the quizzes, assignments, presentations, final essay and class participation.
Passing grades can generally not be earned by students who miss more than 20% of the total class-time.
Make-up exams will not be given unless the student has a medical or other serious reason.
Assignments will be distributed in class or on line. each student must write up his or her answers separately.

Examination topics

Assignments, presentation, class attendance and participation.

Reading list

Wooldridge „Introductory Econometrics“
– Chapters 1-8, 15, 17
Peter Kennedy „A guide to Econometrics“
– Chapters 1-12, 16, 17
Kohler/Kreuter „Data Analysis using Stata“
– Chapter 8 and 9

Association in the course directory

Last modified: Th 03.03.2022 15:47