Because of the COVID-19 pandemic, the course will be organized fully online.
This is a blended learning course that contains both online and in-person elements. All in-person elements are optional, so it is possible to complete the course fully online. While online participation is possible, we follow a schedule, which means that completing the course as independent self-study for credits is not possible.
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, 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 and extensions to binary, count, and categorical variables, and factor analysis, including both exploratory and confirmatory 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.
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.
This course is targeted to industrial engineering and management doctoral students. For DIEM students, the course TU-L0000 - Research Methods in Industrial Engineering and Management is a prerequisite. There are no strict pre-requisites for students outside DIEM, but a background of a basic course in research methods on the Ph.D level is expected.
The course will run also as a parallel instance in University of Jyväskylä under a different code, but using this MyCourses instance.