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220077 UE UE Applied Data Analysis (2019W)
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 16.09.2019 09:00 to Th 31.10.2019 23:59
- Deregistration possible until Th 31.10.2019 23:59
Details
max. 30 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Tuesday 08.10. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Tuesday 15.10. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Tuesday 22.10. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Tuesday 29.10. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Tuesday 05.11. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Tuesday 12.11. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Tuesday 19.11. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Tuesday 26.11. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Tuesday 03.12. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Tuesday 10.12. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Tuesday 17.12. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Tuesday 07.01. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Tuesday 14.01. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Tuesday 21.01. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Tuesday 28.01. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
Information
Aims, contents and method of the course
Assessment and permitted materials
Assessment will be based on the following course requirements:
Participation and Attendance: 20%
Exercises: In-Class / Homework: 80%
Participation and Attendance: 20%
Exercises: In-Class / Homework: 80%
Minimum requirements and assessment criteria
The grading scheme reads as follows:
A = 1 (Very Good): 87 - 100%
B = 2 (Good): 75 - 86,99%
C = 3 (Satisfactory): 63 - 74,99%
D = 4 (Enough): 50 - 62,99%
F = 5 (Not Enough): 00 - 49,99%
Class attendance is mandatory.
A = 1 (Very Good): 87 - 100%
B = 2 (Good): 75 - 86,99%
C = 3 (Satisfactory): 63 - 74,99%
D = 4 (Enough): 50 - 62,99%
F = 5 (Not Enough): 00 - 49,99%
Class attendance is mandatory.
Examination topics
Reading list
Hayes, A. F. (2005). Statistical methods for communication science. Mahwah, NJ: Erlbaum.
Cramer, D. (1998). Fundamental statistics for social research: Step-by-step calculations and computer techniques using SPSS for Windows. New York, NY: Routledge.
Morgan, G. A., Leech, N. L., Gloeckner, G. W., & Barrett, K. C. (2012). IBM SPSS for introductory statistics. Use and interpretation. New York, NY: Routledge.
Cramer, D. (1998). Fundamental statistics for social research: Step-by-step calculations and computer techniques using SPSS for Windows. New York, NY: Routledge.
Morgan, G. A., Leech, N. L., Gloeckner, G. W., & Barrett, K. C. (2012). IBM SPSS for introductory statistics. Use and interpretation. New York, NY: Routledge.
Association in the course directory
Last modified: Sa 02.04.2022 00:23
In sum, the overall goal of the class is to provide students with the necessary conceptual and practical skills to feel comfortable collecting and analyzing data based on their own research questions and designs.In order to do so, the following topics will be covered:Introduction to SPSS
SPSS Data File Creation / Handling
Data Modification and File Management
Frequency, Distribution, and Graphics
Central Tendency and Split Files
Variance, Standard Deviation, and Standard Scores
Correlation
Internal Reliability
Factor Analysis
T-Test
ANOVA
Association versus Causality
Partial Correlation
Linear RegressionAttention: The courses VO Introduction to Data Analysis and UE Applied Data Analysis are linked. Phases of lecture and exercise will alternate.