040195 KU Data Analysis on Organization and Personell (MA) (2019W)

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).

Registration is open from Mo 16.09.2019 09:00 to Mo 23.09.2019 12:00
Registration is open from Th 26.09.2019 09:00 to Fr 27.09.2019 12:00
Deregistration possible until Mo 14.10.2019 12:00

Details

max. 30 participants

Language: English

Lecturers

Yingchao Zhang

Classes (iCal) - next class is marked with N

    
    Thursday
    10.10.
    11:30 - 14:45
    PC-Seminarraum 2  Oskar-Morgenstern-Platz 1  1.Untergeschoß
    
    Thursday
    17.10.
    11:30 - 14:45
    PC-Seminarraum 2  Oskar-Morgenstern-Platz 1  1.Untergeschoß
    
    Thursday
    24.10.
    11:30 - 14:45
    PC-Seminarraum 2  Oskar-Morgenstern-Platz 1  1.Untergeschoß
    
    Thursday
    31.10.
    11:30 - 14:45
    PC-Seminarraum 2  Oskar-Morgenstern-Platz 1  1.Untergeschoß
    
    Wednesday
    20.11.
    09:45 - 20:00
    Seminarraum 5  Oskar-Morgenstern-Platz 1  1.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, 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 econometric 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

Association in the course directory

Last modified: Mo 07.09.2020 15:19