BMT-62406 Small Samples Data Analysis, 3 cr
Additional information
Suitable for postgraduate studies.
Person responsible
Jari Viik
Lessons
Implementation | Period | Person responsible | Requirements |
BMT-62406 2017-01 | 3 |
Jari Viik |
Accepted project work. |
Learning Outcomes
Students can apply both nonparametric statistical methods and basic parametric tests. Students can select and use an appropriate statistical method for analysing small sample data.
Content
Content | Core content | Complementary knowledge | Specialist knowledge |
1. | Nonparametric statistical methods, basic parametric statistical methods,and correlations between parameters. | ||
2. | How to select an appropriate statistical method for analyzing small sample data. |
Instructions for students on how to achieve the learning outcomes
The final grade of the course is determined based on the assessment of all part of the course. The weighting factor of each part is given at the beginning of the course. Grades 1-2: Learning outcomes have been achieved with minimal insufficiency. Satisfactory command in core content of the course. Grades 3-4: Some learning outcomes have been exceeded qualitatively or quantitatively. Good command in core content and complementary knowledge of course content. Good or very good marks from all parts of the course. Grade 5: Most of the learning outcomes have been exceeded. Deep command in the whole content of the course. Almost maximum performance in all parts of the course.
Assessment scale:
Numerical evaluation scale (0-5)
Partial passing:
Study material
Type | Name | Author | ISBN | URL | Additional information | Examination material |
Lecture slides | Yes |
Correspondence of content
Course | Corresponds course | Description |
BMT-62406 Small Samples Data Analysis, 3 cr | ELT-62406 Small Samples Data Analysis, 3 cr | |
BMT-62406 Small Samples Data Analysis, 3 cr | BMT-62416 Small Samples Data Analysis, 5 cr |