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.


This is a basic level course on quantitative research methods in management studies with an emphasis on developing hands-on knowledge in executing and critically assessing survey-based studies. Different to standard courses in statistics, this course is more focused on practical implementation of a quantitative research project in the field of management studies.

The objective of the course is to advance understanding of various principles and practices of quantitative research, and to improve the students readiness to execute a research project in their own discipline.

The main learning outcomes are to gain an understanding of the uses and limitations of common tools for analyzing quantitative data and to develop competence in collecting, modeling, and interpreting quantitative data. Students will improve their capacity to interpret and critically assess methodological execution of empirical management studies. On completion of this course, students are prepared to utilize obtained methodological skills in their master s theses, doctoral dissertations, and/or other research projects.

Credits: 6

Schedule: 01.11.2021 - 03.12.2021

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Alexei Koveshnikov, Roman Stepanov

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


  • valid for whole curriculum period:

    The course covers the fundamentals of the research process, measures development, statistical analysis and modeling of data, and quantitative approaches to research, all with a focus on issues specific to management studies and emphasis on practical experience with application of SPSS analytics software.

    Topics covered in the course include survey research design from hypotheses development to data collection; reliability and validity assessment of multi-item measurement scales; exploratory factor analysis; descriptive analysis of quantitative data; hypotheses testing; linear regression; indirect effects (moderation, mediation); variable transformations. Practical examples and exercises are embedded in the course structure.

Assessment Methods and Criteria
  • valid for whole curriculum period:

    100% assignments

  • valid for whole curriculum period:

    Contact teaching 36h
    Independent work 124h
    Total 160h (6 ECTS)


Study Material
  • valid for whole curriculum period:

    Compulsory readings: Articles included in the syllabus.

    Recommended readings (both textbooks are recommended, although not compulsory, for completing the course assignments): Field, A. (2009) Discovering Statistics Using SPSS. Sage Publications Ltd: London, UK.
    Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014 or any earlier edition) Multivariate data analysis. Pearson Education Limited: Essex, UK.


Substitutes for Courses


Further Information
  • valid for whole curriculum period:

    Max 30 students. 

    Students are admitted to the course in the following priority order: 1) MIB/Global Management/Creative Sustainability, 2) Other School of Business students, 3) Other Aalto students.

    Students must attend the first lecture to ensure their place in the course.
    There is compulsory lecture attendance (85 %), including the last day of the course, when the group presentations are made.

    Teaching Period:

    2020-2021 Autumn II

    2021-2022 Autumn II

    Course Homepage:

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