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Structure Type: Study unit
Code: TK00BG67
Curriculum: TK 2022 / 2023 / 2024
Level: Bachelor of Business Administration
Year of Study: 2 (2023-2024 / 2024-2025 / 2025-2026)
Semester: Autumn
Credits: 2 cr
Responsible Teacher: Siegfrids, Kerstin
Language of Instruction: Finnish


Impl.Group(s)Study TimeTeacher(s)LanguageEnrolment
3001TK2022-2A, TK2022-2B2023-08-21 – 2023-12-17Kerstin SiegfridsFinnish2023-08-01 – 2023-09-06
3002TK2023-2A, TK2023-2B2024-08-19 – 2024-12-15Kerstin SiegfridsFinnish2024-08-01 – 2024-09-06

The descriptions shown below are for the academic year: 2024-2025

Learning Outcomes

The student is able to find statistical data and interpret statistical figures. The student is able to analyze statistical data with different statistics. The student knows the basics of correlation and regression analysis, and is able to run variance analysis and T-test analysis. The student can critically analyze the results acquired from the research.

Student's Workload

54 hours, of which
22 hours of scheduled studies
32 hours of autonomous studies

The assessment of student’s own learning 1 h is included in contact lessons.

Prerequisites / Recommended Optional Courses



Basic terms, statistical charts, parameter estimation, linear regression, dependence analysis, correlation, variance, T-test. Using SPSS in statistical research.

Regional Impact

The examples in the course follow the special aspects of local industry.


Examples emphasize international differences.

Recommended or Required Reading and Other Learning Resources/Tools

Lecture notes

Mode of Delivery / Planned Learning Activities and Teaching Methods

Lectures, exercises

Assessment Criteria

1 the student is able to recognise and use the basic concepts of statistical analysis, and can calculate the most common characteristic values of a given material.
3 the student can carry out a statistical analysis on the internal dependences and influences of a given sample of data, e.g., correlations, regression and the T-test.
5 the student can interpret statistical analyses, draw logical conclusions, and apply the obtained knowledge and skills with challenging statistical samples.

Assessment Methods

Examination, exercises. Numeric scale (0-5).