Applied Statistics
5 credits
Syllabus, Master's level, 1MS026
This course has been discontinued.
A revised version of the syllabus is available.
- Code
- 1MS026
- Education cycle
- Second cycle
- Main field(s) of study and in-depth level
- Mathematics A1N, Mathematics A1N, Technology A1N, Technology A1N
- Grading system
- Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
- Finalised by
- The Faculty Board of Science and Technology, 2 May 2013
- Responsible department
- Department of Mathematics
Entry requirements
120 credits including Probability and Statistics
Learning outcomes
In order to pass the course the student should be able to:
- use the most common statistical tests and understand their assumptions and limitations;
- formulate and choose a suitable methodology for testing in a given situation;
- use the most common estimation methods (e.g. method of moments, or the maximum-likelihood method);
- perform estimation in regression models and evaluate a proposed model;
- evaluate results from statistical software (e.g. R).
Content
Statistical hypothesis testing (interpretation with confidence intervals, p-values), estimation methodology (ML and LS estimation); non-parametric methods, correlation analysis, multiple regression (estimation, prediction, diagnostics).
Instruction
Lectures, computer sessions. Guest lecture. Case studies where the course content is applied in problems arising in technology, the natural or social sciences.
Assessment
Written examination at the end of the course (4 credits) combined with assignments given during the course (1 credit)