220077 UE UE Applied Data Analysis (2017W)
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 18.09.2017 09:00 to We 20.09.2017 18:00
- Deregistration possible until We 20.09.2017 18:00
Details
max. 30 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Tuesday 10.10. 15:00 - 16:30 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Tuesday 17.10. 15:00 - 16:30 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Tuesday 24.10. 15:00 - 16:30 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Tuesday 31.10. 15:00 - 16:30 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Tuesday 07.11. 15:00 - 16:30 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Tuesday 14.11. 15:00 - 16:30 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Tuesday 21.11. 15:00 - 16:30 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Tuesday 28.11. 15:00 - 16:30 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Tuesday 05.12. 15:00 - 16:30 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Tuesday 12.12. 15:00 - 16:30 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Tuesday 09.01. 15:00 - 16:30 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Tuesday 16.01. 15:00 - 16:30 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Tuesday 23.01. 15:00 - 16:30 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Tuesday 30.01. 15:00 - 16:30 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
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%
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%
Examination topics
Reading list
Association in the course directory
Last modified: Mo 07.09.2020 15:39
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 RegressionAttention: The courses VO Introduction to Data Analysis and UE Applied Data Analysis are linked. Phases of lecture and exercise will alternate.