350093 SE MSC.III - Quantitative research methods (2022W)
Continuous assessment of course work
Labels
MIXED
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 05.09.2022 09:00 to We 21.09.2022 12:00
- Deregistration possible until Mo 31.10.2022 12:00
Details
max. 20 participants
Language: German
Lecturers
Classes (iCal) - next class is marked with N
- Friday 07.10. 10:00 - 13:00 ZSU - USZ II, EDV Raum, 2. Stock
- Friday 11.11. 10:00 - 13:00 ZSU - USZ II, EDV Raum, 2. Stock
- Friday 25.11. 10:00 - 13:00 ZSU - USZ II, EDV Raum, 2. Stock
- Friday 02.12. 09:00 - 12:00 ZSU - USZ II, EDV Raum, 2. Stock
- Friday 16.12. 10:00 - 13:00 ZSU - USZ II, EDV Raum, 2. Stock
- Friday 13.01. 10:00 - 13:00 ZSU - USZ II, EDV Raum, 2. Stock
- Friday 27.01. 10:00 - 13:00 ZSU - USZ II, EDV Raum, 2. Stock
Information
Aims, contents and method of the course
Assessment and permitted materials
Homeworks, interim tests, final test-) homeworks (20%)
-) theoretical knowledge (20%)
-) Final test as individual work (60%, can be repeated in any case) - min. 36 out of 60 points; 30 - 35.99 points: Overall grade -1; < 30 points: Test must be repeated)
-) theoretical knowledge (20%)
-) Final test as individual work (60%, can be repeated in any case) - min. 36 out of 60 points; 30 - 35.99 points: Overall grade -1; < 30 points: Test must be repeated)
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%The entire completion of tasks by students must take place by the following April 30th for courses with continous 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).
Nicht genügend (5): <60%
Genügend (4): 60-70%
Befriedigend (3): 71-80%
Gut (2): 81-90%
Sehr gut (1): 91-100%The entire completion of tasks by students must take place by the following April 30th for courses with continous 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).
Examination topics
Slides and materials as provided in the seminarSPSS application (Attention: You would need a SPSS Statistics Software licence, https://zid.univie.ac.at/en/software-for-students/user-guides/spss-statistics/)
Reading list
Field, A. (2013). Discovering statistics using IBM SPSS statistics, 4. Aufl., SAGEO'Donoghue, P. (2012). Statistics for Sport and Exercise Studies: An Introduction, RoutledgeHopkins, W.G. (2013). A new view of statistics. http://www.sportsci.org/resource/stats/
Association in the course directory
MSC.III
Last modified: We 18.01.2023 17:29
-) Secure application of quantitative methods in empirical research
-) Capability to interpret statistical measures in sport scientific articles
-) Ability to autonomously analyse and show empirical data
Content:
-) Statistics software SPSS
-) Statistical procedures (descriptive analyses, inferential statistics, correlation/regression)
-) Statistical methods within the research process (study planning, analyses and interpretation)
Methods:
-) autonomous and instructed work at the PC