Universität Wien FIND

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040195 KU Data Analysis on Organization and Personell (MA) (2017W)

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 05.10. 09:45 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 05.10. 11:30 - 13:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 12.10. 09:45 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 12.10. 11:30 - 13:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 19.10. 09:45 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 19.10. 11:30 - 13:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 09.11. 09:45 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 09.11. 11:30 - 13:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 16.11. 09:45 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 16.11. 11:30 - 13:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 23.11. 09:45 - 16:45 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.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, 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.

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

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.

Examination topics

quiz, assignments, final essay, class attendance and participation.

Reading list

Required Texts:
Jeffrey Wooldridge, Introductory Econometrics, A Modern Approach, 4th edition, South-Western Cengage Learning Co. 2013.
Software:
The course statistical software is STATA, which is available on the computer lab. The data for the problem sets will be posted on the course Web page. You may purchase STATA through www.stata.com at an academic price but this is strictly optional.
http://www.stata.com/order/new/edu/gradplans/student-pricing/ (Small Stata 13, student version, $35 – 49).

Association in the course directory

Last modified: Mo 07.09.2020 15:28