350190 SE MSC.III - Quantitative Research Methods (2023S)
Continuous assessment of course work
Labels
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 06.02.2023 09:00 to We 22.02.2023 12:00
- Registration is open from We 01.03.2023 09:00 to We 08.03.2023 12:00
- Deregistration possible until Fr 31.03.2023 12:00
Details
max. 20 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Thursday 02.03. 13:00 - 16:00 ZSU - USZ II, EDV Raum, 2. Stock
- Thursday 16.03. 13:00 - 16:00 ZSU - USZ II, EDV Raum, 2. Stock
- Thursday 30.03. 13:00 - 16:00 ZSU - USZ II, EDV Raum, 2. Stock
- Thursday 20.04. 13:00 - 16:00 ZSU - USZ II, EDV Raum, 2. Stock
- Thursday 04.05. 13:00 - 16:00 ZSU - USZ II, EDV Raum, 2. Stock
- Thursday 01.06. 13:00 - 16:00 ZSU - USZ II, EDV Raum, 2. Stock
- Thursday 15.06. 13:00 - 16:00 ZSU - USZ II, EDV Raum, 2. Stock
Information
Aims, contents and method of the course
Assessment and permitted materials
Course assessment will be based on homework, interim tests, and a final test.- Homework (20%)
- Theoretical knowledge (20%)
- Final test (60%, can be repeated)The entire completion of tasks by students must take place by the following April 30th for courses with continuous assessment in the winter semester, and by September 30th at the latest for those in the summer semester. Students who did not sign out from the course are to be assessed. In the case of a negative assessment, an examination before a committee is not permitted; the course must be repeated. Legal source: Statutes of the University of Vienna §10 (4, 5, 6).You are expressly pointed out that if a result was obtained by fraudulent means (e.g. copying, plagiarism, use of unauthorized aids, forgeries, ghostwriting, etc.), the entire PI-LV is considered cheated and counts as a trial. (Entry in U: SPACE: X = not assessed).
- Theoretical knowledge (20%)
- Final test (60%, can be repeated)The entire completion of tasks by students must take place by the following April 30th for courses with continuous assessment in the winter semester, and by September 30th at the latest for those in the summer semester. Students who did not sign out from the course are to be assessed. In the case of a negative assessment, an examination before a committee is not permitted; the course must be repeated. Legal source: Statutes of the University of Vienna §10 (4, 5, 6).You are expressly pointed out that if a result was obtained by fraudulent means (e.g. copying, plagiarism, use of unauthorized aids, forgeries, ghostwriting, etc.), the entire PI-LV is considered cheated and counts as a trial. (Entry in U: SPACE: X = not assessed).
Minimum requirements and assessment criteria
Attendance is compulsory (at least 75% of the units).The minimum requirement for a positive assessment is 60% of the total points.Grading:
Nicht genügend (5): <60%
Genügend (4): 60-70%
Befriedigend (3): 71-80%
Gut (2): 81-90%
Sehr gut (1): 91-100%
Nicht genügend (5): <60%
Genügend (4): 60-70%
Befriedigend (3): 71-80%
Gut (2): 81-90%
Sehr gut (1): 91-100%
Examination topics
Slides and materials as provided in the seminar.SPSS application (Attention: you would need an SPSS Statistics Software license, https://zid.univie.ac.at/en/software-for-students/user-guides/spss-statistics/).
Reading list
Field, A. (2018). Discovering statistics using IBM SPSS statistics, 5. ed., SAGE
O'Donoghue, P. (2012). Statistics for Sport and Exercise Studies: An Introduction, Routledge
Hopkins, W.G. (2013). A new view of statistics. http://www.sportsci.org/resource/stats/
O'Donoghue, P. (2012). Statistics for Sport and Exercise Studies: An Introduction, Routledge
Hopkins, W.G. (2013). A new view of statistics. http://www.sportsci.org/resource/stats/
Association in the course directory
MSC.III
Last modified: Tu 14.03.2023 13:09
- Confident application of quantitative methods in empirical research
- Competence in interpreting statistical measures in Sport Science-related literature
- Ability to autonomously analyze and present empirical dataContent:
- Use of the SPSS statistical analysis tool
- Statistical methods (descriptive analyses, correlation/regression, and inferential statistics)
- Application of these statistical methods within the research process (study planning, analyses, and interpretation)Methods:
- Autonomous and guided work at the PC