400002 SE SE Methods for Doctoral Candidates (2011W)

Explorative Data Analysis

4.00 ECTS (2.00 SWS), SPL 40 - Doktoratsstudium Sozialwissenschaften

Continuous assessment of course work

DO wtl ab 13.10.2011, 14.00 - 15.30
Ort: NIG, Kursraum A, EG Stiege rechts

Moodle

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 We 28.09.2011 12:54 to Fr 07.10.2011 12:54
Deregistration possible until Fr 07.10.2011 12:54

Details

max. 15 participants

Language: English

Lecturers

Eva Zeglovits

Classes

Currently no class schedule is known.

Information

Aims, contents and method of the course

Explorative methods in data analysis aim at detecting patterns in data set and reducing complexity. Exploratory factor analysis is used to find latent structures behind a set of observed (manifest) variables, for example to bundle a number of variables to a common attitude behind them. Cluster analysis is usually used to group objects or persons of an heterogenous population to a finite number of homogenous clusters.
The course shall give an insight to the priciples of exploratory methods and critically discuss the merits and limits of exploratory approaches. STATA will be used to do exercises. Students are invited to bring their own data sets and research questions, although data sets will be provided for the excercises.

Assessment and permitted materials

presentations of own examples (2 times), written paper (10-20 pages)

Minimum requirements and assessment criteria

Verständnis der Prinzipien von explorativer Faktorenanalyse und Clusteranalyse; kritische Reflexion der Möglichkeiten und Risiken bei der Anwendung; praktische Umsetzung in STATA

Examination topics

Input by the trainer, discussion, practical sessions in the computer lab, analysing and presenting one's own examples

Reading list

Bacher/Pöge/Wenzig (2010): Clusteranalyse. Anwendungsorientierte Einführung in Klassifikationsverfahren. 3. Auflage. Oldenburg
Backhaus et al. (2008): Multivariate Analysemethoden: Eine anwendungsorientierte Einführung. Springer.
Foster/Barkus/Yavorsky (2006): Understanding and Using Advanced Statistics. SAGE
Hair, J.F. et al (1995) Multivariate Data Analysis with Readings, London, Prentice-Hall

Association in the course directory

Last modified: Mo 07.09.2020 15:46