JSBJ1310 Statistical Research Methods (5–8 cr)

Open the course unit brochure on Sisu

Study level:

Postgraduate studies

Grading scale:

0-5

Language:

English

Responsible organisation:

Jyväskylä University School of Business and Economics

Curriculum periods:

2024-2025, 2025-2026, 2026-2027, 2027-2028

Description

Causality, three conditions for demonstrating it
Statistical inference and causal inference
Regression analysis, including diagnostics and interpretation
Moderation, mediation, and instrumental variables
Generalized linear and other non-linear models
Reliability and validity
Measurement and measurement validation
Factor analysis
Research design
Research ethics

Learning outcomes

The course aims to equip students with a comprehensive understanding of how statistical methods are practically applied in management and social research and how these results are typically presented in journal articles. This course is tailored for those interested in comprehending research conducted with statistical methods and those already using or planning to use statistical research methods in their professional endeavors.

Throughout the course, we will delve into empirical papers published in renowned journals such as the Academy of Management Journal and Strategic Management Journal, among others. We will analyze the methodologies and research designs employed in these papers, which encompass a wide range of basic methods and designs commonly used in these reputable journals.

The analysis techniques covered during the course include regression analysis, its application moderation, mediation, basic non-linear models, and factor analysis, focusing on exploratory factor analysis. Confirmatory factor analysis is explained on a surface level sufficient for its basic application and evaluation of published results. Extensions of these techniques, such as structural regression models (structural equation models) or multilevel models and other similar methods for non-independent observations (e.g., longitudinal or multilevel data), are briefly introduced, but a more thorough study of these techniques is left for advanced courses. The data analysis assignments can be completed with Stata, R, or SPSS.

Additional information

The course normally runs from November to April every academic year. The pre-exam must be completed in December. Contact teaching will start in January. The course may also run on a different schedule.

Study materials

The reading materials consists of articles, book, and book chapters on research design and analysis. The course follows a blended learning where the traditional lecture content is delivered as prerecorded videos. The video materials include over a 100 lectures of varying length.

Completion methods

Method 1

Description:

Pre-exam, video lectures, online participation, readings and written assignments, seminars (either in person or over Zoom), optional computer class sessions, data-analysis assignments, and learning diary.

Evaluation criteria:

The course is assessed on the basis of how the doctoral student masters the contents of the study unit and achieves the learning outcomes of the study unit. Seminar participation, assignments, pre-exam, and learning diary are considered in the assessment.

Select all marked parts

Parts of the completion methods

Participation in teaching (5–8 cr)

Type:

Participation in teaching