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Course Catalog 2014-2015
ELT-62406 Small Samples Data Analysis, 3 cr |
Additional information
Suitable for postgraduate studies
Person responsible
Jari Viik
Lessons
| Study type | P1 | P2 | P3 | P4 | Summer | Implementations | Lecture times and places |
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Requirements
Accepted assignments and final exam.
Completion parts must belong to the same implementation
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 analysing 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 (1-5) will be used on the course
Partial passing:
Study material
| Type | Name | Author | ISBN | URL | Edition, availability, ... | Examination material | Language |
| Lecture slides | Yes | English |
Prerequisite relations (Requires logging in to POP)
Correspondence of content
There is no equivalence with any other courses
More precise information per implementation
| Implementation | Description | Methods of instruction | Implementation |
| Student can apply nonparametric statistical methods and basic parametric tests. Student can select and use an appropriate statistical method for analysing small sample data. | Lectures Excercises Practical works |
Contact teaching: 0 % Distance learning: 0 % Self-directed learning: 0 % |