220077 UE UE Applied Data Analysis (2019W)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 16.09.2019 09:00 bis Do 31.10.2019 23:59
- Abmeldung bis Do 31.10.2019 23:59
Details
max. 30 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
- Dienstag 08.10. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Dienstag 15.10. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Dienstag 22.10. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Dienstag 29.10. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Dienstag 05.11. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Dienstag 12.11. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Dienstag 19.11. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Dienstag 26.11. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Dienstag 03.12. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Dienstag 10.12. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Dienstag 17.12. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Dienstag 07.01. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Dienstag 14.01. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Dienstag 21.01. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
- Dienstag 28.01. 19:45 - 21:15 Seminarraum 1 2H316 UZA II Rotunde
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
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%
Mindestanforderungen und Beurteilungsmaßstab
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.
Prüfungsstoff
Literatur
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.
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: 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.