Universität Wien
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220077 UE UE Applied Data Analysis (2019W)

Continuous assessment of course work

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).

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

The objective of this class is to make students acquaintance with basic theoretical and practical statistical and quantitative research concepts in communication research. After the completion of the class, students should be able to plan and construct most commonly needed quantitative analyses in our field based on their own quantitative research designs.

The content of the class will generically cover fundamental mathematical processes for all statistical tests. However, more emphasis will be placed on the general understanding of all necessary methodological concepts to execute quantitative empirical tests with SPSS.

Students will be proficient interpreting SPSS outputs, creating tables ready to be published in academic journals, and discussing as well as interpreting most common quantitative findings in our field.
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 Regression

Attention: The courses VO Introduction to Data Analysis and UE Applied Data Analysis are linked. Phases of lecture and exercise will alternate.

Assessment and permitted materials

Assessment will be based on the following course requirements:
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.

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.

Association in the course directory

Last modified: Sa 02.04.2022 00:23