Advanced Statistics

Department

Master's Program International Health & Social Management

Course unit code

IHSM-M2.2

Number of ECTS credits allocated

5.0

Name of lecturer(s)

FH-Prof. Dr. Mevenkamp Nils

Mode of delivery

-

Recommended optional program components

none

Recommended or required reading

Bruce, N., Pope, D., & Stanistreet, D. (2008). Quantitative methods for health research: A practical interactive guide to epidemiology and statistics. Chichester: Wiley.
Diez, D. M., Barr, C. D., & Cetinkaya-Rundel, M. (2015). OpenIntro Statistics. URL: https://www.openintro.org/stat/textbook.php
Field, A. (2009). Discovering statistics using SPSS: (and sex and drugs and rock'n'roll) (3rd ed.). Los Angeles, Calif.: Sage.
Flick, U. (2011). Introducing research methodology: A beginner's guide to doing a research project. Los Angeles: Sage.
Lane, D. M. Online Statistics Education: A Multimedia Course of Study. URL: http://onlinestatbook.com/
Lowry, R. (1998-2013). Concepts and Applications of Inferential Statis-tics. URL: http://vassarstats.net/textbook/
Siegel, S. (1956). Nonparametric Statistics for the Behavioral Scienc-es. New York u.a.: McGraw-Hill.

Level of course unit

Master

Year of study

Spring 2026

Semester when the course unit is delivered

2

Language of instruction

English

Learning outcomes of the course unit

By the end of this course, students will be able to:
• demonstrate basic knowledge and awareness of the role of mul-tivariate statistics in public health
• understand concepts and applications of statistical models
• understand and critically reflect empirical studies in the field of public health

Course contents

• Introduction & Repetition of Basic Concepts: Frequency distribu-tions, descriptive statistics, random sampling, theoretical distribu-tions, central limit theorem, hypothesis testing
• Test hypotheses of differences: Contingency tables, chi-square-tests, rank size analysis, Compare means, t-test, ANOVA
Test hypotheses of associations: Simple & multiple regression, nonlinear transformations
Logistic regression: Contingency tables & odds ratios, multiple binary logistic regression
Questionnaires: Questionnaire design, dos & don'ts in survey based research
Indirect measurement of complex dimensions: Likert scaling, sum scores, reliability analysis, Cronbach's alpha
Validation of item sets: Concepts of validity, factor analysis

Planned learning activities and teaching methods

The course comprises an interactive mix of lectures, discussions and individual and group work.

Work placement(s)

none