Quantitative methods II: Inferential statistics & test procedures
Niveau
Bachelor
Learning outcomes of the courses/module
The students
• are familiar with the basic principles and applications of analysis of variance (ANOVA) as well as relevant test procedures for rank and nominal data.
• understand the techniques and assumptions of linear and non-linear regression analysis, including special models such as logistic regression.
• can conduct and interpret statistical analyses using advanced regression models.
• understand the fundamentals of questionnaire construction, including item and construct development, as well as the application of psychometric test procedures.
• can apply and conduct quality criteria for psychological tests, supported by factor analyses and reliability analyses.
• are familiar with the basic principles and applications of analysis of variance (ANOVA) as well as relevant test procedures for rank and nominal data.
• understand the techniques and assumptions of linear and non-linear regression analysis, including special models such as logistic regression.
• can conduct and interpret statistical analyses using advanced regression models.
• understand the fundamentals of questionnaire construction, including item and construct development, as well as the application of psychometric test procedures.
• can apply and conduct quality criteria for psychological tests, supported by factor analyses and reliability analyses.
Prerequisites for the course
None
Course content
• Analysis of Variance (ANOVA) (one-way, two-way, and multifactorial; Types of Effects; Mean Comparison or t-Test; F-Test; Post-hoc Analyses; Analyses with and without repeated measures)
• Methods for Ranked Data (Mann-Whitney U Test; Wilcoxon Test; Kruskal-Wallis H Test) and Methods for Nominal Data (Chi-Square Test; Effect Size)
• Regression Analysis (univariate and multivariate linear regression; Non-linear Relationships; Dummy Variables; Interaction Variables; Assumptions Testing; Alternative Models to Linear Regression; Advanced Regression Models [e.g., Logit Regression, Quantile Regression, etc.])
• Questionnaire Construction and Testing Procedures (Criteria for Good Measurement; Variables, Items, and Constructs; Descriptive Statistical Item Analysis & Test Score Determination; Standards for Psychological Testing; Test Theories; Confirmatory & Exploratory Factor Analysis; Reliability Analysis; Semantic Differential)
The deepening of (theoretical) content is achieved through practical examples including software support.
• Methods for Ranked Data (Mann-Whitney U Test; Wilcoxon Test; Kruskal-Wallis H Test) and Methods for Nominal Data (Chi-Square Test; Effect Size)
• Regression Analysis (univariate and multivariate linear regression; Non-linear Relationships; Dummy Variables; Interaction Variables; Assumptions Testing; Alternative Models to Linear Regression; Advanced Regression Models [e.g., Logit Regression, Quantile Regression, etc.])
• Questionnaire Construction and Testing Procedures (Criteria for Good Measurement; Variables, Items, and Constructs; Descriptive Statistical Item Analysis & Test Score Determination; Standards for Psychological Testing; Test Theories; Confirmatory & Exploratory Factor Analysis; Reliability Analysis; Semantic Differential)
The deepening of (theoretical) content is achieved through practical examples including software support.
Recommended specialist literature
• Haslam, A. S., McGarty, C., Cruwys, T., & Steffens, N. K. (2024). Research methods and statistics in psychology. London: Sage.
• Moosbrugger, H., & Kelava, A. (2020) (Hrsg.). Testtheorie und Fragebogenkonstruktion. Berlin: Springer
• Rasch, B., Friese, M., Hofmann, W., & Naumann, E. (2021). Quantitative Methoden 2: Einführung in die Statistik für Psychologie, Sozial- & Erziehungswissenschaften. Berlin: Springer.
• Rasch, B., Friese, M., Hofmann, W., & Naumann, E. (2021). Quantitative Methoden 1: Einführung in die Statistik für Psychologie, Sozial- & Erziehungswissenschaften. Berlin: Springer.
• Moosbrugger, H., & Kelava, A. (2020) (Hrsg.). Testtheorie und Fragebogenkonstruktion. Berlin: Springer
• Rasch, B., Friese, M., Hofmann, W., & Naumann, E. (2021). Quantitative Methoden 2: Einführung in die Statistik für Psychologie, Sozial- & Erziehungswissenschaften. Berlin: Springer.
• Rasch, B., Friese, M., Hofmann, W., & Naumann, E. (2021). Quantitative Methoden 1: Einführung in die Statistik für Psychologie, Sozial- & Erziehungswissenschaften. Berlin: Springer.
Assessment methods and criteria
• Quiz
• Seminar Paper
• Seminar Paper
Language
German
Number of ECTS credits awarded
6
Share of e-learning in %
20
Semester hours per week
4.0
Planned teaching and learning method
20% of the course will be covered through eLearning. This will involve a combination of online phases (inductive method for independent acquisition of knowledge and practicing tasks) and face-to-face sessions (deductive method providing assistance in the learning process and imparting knowledge through lectures).
Semester/trimester in which the course/module is offered
2
Name of lecturer
STGL
Academic year
1
Key figure of the course/module
QQM2
Type of course/module
integrated lecture
Type of course
Compulsory
Internship(s)
-