Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

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: 8

Schedule: 02.11.2021 - 06.04.2022

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 in-person elements can be completed either at Aalto University in Espoo or at University of Jyva skyla and participants can obtain credits from either of these universities. A fully online participation is possible, but we follow a schedule, which means that completing the course as independent self- study for credits is not possible. Participating in the seminars is compulsory for Aalto DIEM post-graduate students.

    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
Prerequisites

FURTHER INFORMATION

Further Information
  • valid for whole curriculum period:

    Teaching Period:

    2020-2021 Spring III-IV

    2021-2022 Spring III-IV

    Course Homepage: https://mycourses.aalto.fi/course/search.php?search=TU-L0022

    Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.

    The course is offered for doctoral students.