Statistics
| Structure Type: | Study unit |
|---|---|
| Code: | TK00BG67 |
| Curriculum: | TK 2022 |
| Level: | Bachelor of Business Administration |
| Year of Study: | 2 (2023-2024) |
| Semester: | Autumn |
| Credits: | 2 cr |
| Responsible Teacher: | Siegfrids, Kerstin |
| Language of Instruction: | Finnish |
Courses During the Academic Year 2023-2024
| Impl. | Group(s) | Study Time | Teacher(s) | Language | Enrolment |
|---|---|---|---|---|---|
| 3001 | TK2022-2A, TK2022-2B | 2023-08-21 – 2023-12-17 | Kerstin Siegfrids | Finnish | 2023-08-01 – 2023-09-06 |
Still need to take the course? See the courses during 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
-
Contents
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.
Internationality
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).