Universität Wien

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

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Prüfungsimmanente Lehrveranstaltung

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

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 25 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine

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

Ziele, Inhalte und Methode der Lehrveranstaltung

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 should 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.

Art der Leistungskontrolle und erlaubte Hilfsmittel

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.

Mindestanforderungen und Beurteilungsmaßstab

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.

Prüfungsstoff

Assignments, presentation, class attendance and participation.

Literatur

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

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Do 03.03.2022 15:47