LEARNING OUTCOMES
The goal of the course is to develop an understanding of how statistical methods are used in management and other social research and how results are usually presented in journal articles. The course is designed for both those interested in just reading and understanding research done with statistical methods and for those who already use or plan to use statistical research methods in their own work.
During the course we will go through empirical papers published in Academy of Management Journal and Strategic Management Journal, and other high-quality journals and analyze how these papers were done. The methods and research designs used in these papers cover a majority of basic methods and designs used in these journals.
The analysis techniques covered during the course include regression analysis, its application moderation, mediation, and basic non-linear models, and factor analysis, focusing on exploratory factor analysis. Confirmatory factor analysis is explained on a surface level that is 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 or other similar techniques 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.
Credits: 5 - 8
Schedule: 18.11.2024 - 16.04.2025
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Mikko Rönkkö
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
This is a blended learning course that contains both online and in-person elements.
The course consists of eight units, that each take two to four weeks and contain video lectures, online and in-person discussions, and assignments. The number of credits varies between 5-8 depending on which assignments students choose to complete. The content of each course component is explained later in the course brochure. The data analysis assignments can be completed with Stata, R, or SPSS, but SPSS is not recommended.
Assessment Methods and Criteria
valid for whole curriculum period:
Class participation, online participation, lecture diary, pre-lecture assignments, data analysis assignments, and pre-exam.
Workload
valid for whole curriculum period:
See syllabus.
DETAILS
Study Material
valid for whole curriculum period:
Video lectures, empirical articles, methodological articles, books about methods. See the course syllabus for details.
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language: English
Teaching Period: 2024-2025 Spring III - IV
2025-2026 Spring III - IV