Research Methods, Psychometrics, and Data Analysis for Organizational Psychology

Introduction

The purpose of this course is to equip students with the knowledge and skills required to conduct high-quality research in organizational psychology. The course supports the development of competence in research design, psychometrics, and data analysis relevant for empirical thesis work. A central aim is to foster the ability to critically evaluate organizational psychology research, including theoretical assumptions, measurement quality, and analytical choices. The course has a strong applied orientation, combining conceptual foundations with hands-on experience working with data. In addition to quantitative research methods and statistical modeling, the course includes an introduction to qualitative approaches. Through applied exercises, students learn how different methodological approaches can be used to generate rigorous and actionable knowledge for organizational and applied research contexts.

Course content

The course covers central methodological and analytical topics in organizational psychology, spanning quantitative and qualitative research approaches. Core themes include research questions and designs, internal and external validity, and ethical considerations in research. The course introduces key quantitative methods commonly used in organizational research, including regression and logistic regression, mediation and moderation, construct validity, and factor analysis, as well as an overview of structural equation and multilevel models. Qualitative components include qualitative research designs, semi-structured interviews, qualitative analysis, and case study research. The course concludes with an exam preparation lecture that integrates the course content and highlights key areas for revision.

The course addresses the following topics in lectures/seminars:

1. Introduction to organizational behaviour research and data analysis
2. Research questions and research designs
3. Internal and external validity
4. Seminar 1: Introduction to Jamovi/R/Stata and data management
5. Seminar 2: Graphs, descriptives, tabulating data and comparing groups
6. Regression and logistic regression
7. Mediation and moderation
8. Construct validity and factor analysis
9. Structural equation modelling and multilevel models
10. Qualitative research designs
11. Semi-structured interviews
12. Qualitative analysis
13. Case study research
14. Research ethics
15. Exam preparation lecture

Disclaimer

This is an excerpt from the complete course description for the course. If you are an active student at BI, you can find the complete course descriptions with information on eg. learning goals, learning process, curriculum and exam at portal.bi.no. We reserve the right to make changes to this description.