040217 KU Data Analysis on Organization and Personnel (MA) (2024S)
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 12.02.2024 09:00 to We 21.02.2024 12:00
- Registration is open from Mo 26.02.2024 09:00 to Tu 27.02.2024 12:00
- Deregistration possible until Th 14.03.2024 23:59
Details
max. 25 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Friday
01.03.
15:00 - 16:30
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Friday
01.03.
16:45 - 18:15
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday
25.04.
16:45 - 18:15
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Friday
26.04.
15:00 - 16:30
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Friday
26.04.
16:45 - 18:15
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
N
Friday
24.05.
15:00 - 16:30
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Friday
24.05.
16:45 - 18:15
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Friday
31.05.
15:00 - 16:30
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Friday
31.05.
16:45 - 18:15
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday
20.06.
16:45 - 18:15
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Friday
21.06.
15:00 - 16:30
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Friday
21.06.
16:45 - 18:15
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday
27.06.
16:45 - 18:15
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Friday
28.06.
15:00 - 16:30
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Friday
28.06.
16:45 - 18:15
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Information
Aims, contents and method of the course
Assessment and permitted materials
Your final grade is determined by your performance on the quizzes, assignments, final report 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.
1 (very good) → 100-89 points
2 (good) → 88-76 points
3 (satisfactory) → 75-63 points
4 (enough) → 62-50 points
5 (not enough) → 49-0 points
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.
1 (very good) → 100-89 points
2 (good) → 88-76 points
3 (satisfactory) → 75-63 points
4 (enough) → 62-50 points
5 (not enough) → 49-0 points
Minimum requirements and assessment criteria
Basic knowledge of Business Mathematics and Statistics are required.
Passing grades can generally not be earned by students who miss more than 20% of the total class-time.
Passing grades can generally not be earned by students who miss more than 20% of the total class-time.
Examination topics
Assignments, presentations, in class discussion and participation.
Reading list
Wooldridge "Introductory Econometrics"
Association in the course directory
Last modified: Fr 01.03.2024 14:45
The course aims to provide participants with a basic understanding of the quantitative research process—from the development of a research question with associated hypotheses to the evaluation and interpretation of the results. Particular emphasis is placed on understanding the procedures and basic applications as well as the interpretation of empirical results. The following topics are covered using examples.
• From the problem to the question: How do I develop a research question and derive hypotheses from it?
• Method selection and collection: Which data collection methods are available to me and which is best suited to answer my research question?
• Hypothesis testing: Which statistical methods are available to me? Which ones are best suited to test my hypotheses?
• Interpretation: What do my results mean? Which statements and conclusions are permissible and which are not?