Humboldt-Universität zu Berlin - Statistik

Datenanalyse II (VL+UE)

The lecture covers classical statistical topics and we will work half of the time with SPSS and/or R in a PC-Pool. Note: The lecture will be hold in german, but slides and exercise will be in english.

Bitte registrieren Sie sich im zugehörigen Moodle-Kurs.

Data analysis I:

  • Survey design
    • Operationalization
    • Validity 
  • Short repetition of Statistics I+II
    • Sampling
    • Scaling
    • Test theory
    • Estimation theory
  • Identification of outliers
  • Treatment of missing values
    • Types (MAR, MCAR, MNAR)
    • Imputation methods (single, multiple)
  • Univariate statistics
    • Graphical representation (stem-and-leaf, strip plot, kernel density, violin plot)
    • Coeffcients (quantile, entropy, higher moments, hinges and spreads)
    • Tests (t-Tests, Mann-Withney-U, Median, Wilcoxon, Kruskal-Wallis, ANOVA, Friedman)
    • Transformations (Power, Box-Cox)
    • Robust coefficients for location and dispersion (L- and M-estimators for location)
  • Bivariate statistics
    • Graphical representation (sunflower plot, mosaic plot, trellis display)
    • Subgroup analysis

Data analysis II:

  • Bivariate statistics
    • Coeffcients and tests (association and PRE- measure, Cohen's kappa, relative risk, odds ratio)
  • Multivariate statistics
    • Principal component analysis
    • Exploratory factor analysis (reliability for sum scores)
    • Cluster analysis
  • Regression methods
    • Simple linear regression
    • Multiple linear regression
    • Generalized linear regression
    • Non- and Semiparametric Regression
    • Classification and regression trees
    • Neural networks
  • Latent variable models
    • Item-Response-Theory


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  • Berry, D.A., Lindgren, B.W. (1990), Statistics: Theory and Methods, Brooks/Cole Publishing Company, Pacific Grove
  • Bortz, J. (1993), Statistik, Springer, Berlin et al.
  • Bosch, K. (1992), Statistik-Taschenbuch, Oldenbourg, München, Wien
  • Bühl, A., Zöfel, P. (1994), SPSS unter Windows Version 6, Addison-Wesley, Bonn et al.
  • Böning, H., Trenkler, G. (1978), Nichtparametrische statistische Methoden, Walter de Gruyter, Berlin, New York
  • Böning, H. (1991), Robuste und adaptive Tests, Walter de Gruyter, Berlin, New York
  • Hartung, J., Elpelt, B., Klösener, K.-H. (1993), Statistik, Oldenbourg Verlag, München
  • Heiler, S., Michels, P. (1994), Deskriptive und explorative Datenanalyse, Oldenbourg, München, Wien
  • Jobson, J.D. (1991), Applied Multivariate Data Analysis, Vol. I: Regression and Experimental Design, Springer, Berlin et al.
  • Köhler, W.-M. (1994), SPSS für Windows, Vieweg, Wiesbaden
  • Mann, P. S. (1992), Introductory Statistics, John Wiley, New York at al.
  • Rasmussen, S. (1992), An Introduction to Statistics with Data Analysis, Brooks/Cole Publishing Company, Pacific Grove
  • Rönz: Skript zur Vorlesung "Computergestützte Statistik I", 2001
  • Rönz, B., Strohe, H. G. (Hrsg., 1994), Lexikon Statistik, Gabler-Verlag, Wiesbaden
  • Schlittgen, R. (1990), Einführung in die Statistik, Oldenbourg, München, Wien