Universität Wien FIND

Due to the COVID-19 pandemic, changes to courses and exams may be necessary at short notice (e.g. cancellation of on-site teaching and conversion to online exams). Register for courses/exams via u:space, find out about the current status on u:find and on the moodle learning platform. NOTE: Courses where at least one unit is on-site are currently marked "on-site" in u:find.

Further information about on-site teaching and access tests can be found at https://studieren.univie.ac.at/en/info.

040217 KU Data Analysis on Organization and Personell (MA) (2020S)

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

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

Registration/Deregistration

Details

max. 25 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

learning at home and e-learning

Dear Students,

As from 11 March 2020 until 3 April 2020, no courses/exams with student attendance will take place at the University of Vienna. Teaching will instead take place in the form of learning at home and e-learning. Please check on Moodle for the learning at home material, such as lecture notes, execises do files, papers and if you would like to practice with these exercises, these is Stata student Version online.

please check Moodle and your university email account for any updated information.

Wednesday 04.03. 13:15 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday 11.03. 13:15 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday 18.03. 13:15 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday 25.03. 13:15 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 30.03. 09:45 - 13:00 Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Stock
Monday 30.03. 13:15 - 20:00 Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Stock

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, final essay 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.

Exam review is possible during regular semester time by appointment.

Examination topics

assignments, presentation, final essay, 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: Mo 07.09.2020 15:19