040217 KU Data Analysis on Organization and Personell (MA) (2020S)
Continuous assessment of course work
Labels
service email address: opim.bda@univie.ac.at
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 10.02.2020 09:00 to We 19.02.2020 12:00
- Registration is open from Tu 25.02.2020 09:00 to We 26.02.2020 12:00
- Deregistration possible until Th 30.04.2020 23:59
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
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.
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.
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
– 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
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.