Regression Analysis
5 credits
Syllabus, Bachelor's level, 1MS555
A revised version of the syllabus is available.
- Code
- 1MS555
- Education cycle
- First cycle
- Main field(s) of study and in-depth level
- Mathematics G2F
- Grading system
- Pass with distinction (5), Pass with credit (4), Pass (3), Fail (U)
- Finalised by
- The Faculty Board of Science and Technology, 10 March 2016
- Responsible department
- Department of Mathematics
Entry requirements
60 credits in mathematics including Probability Theory I and Inference Theory I.
Learning outcomes
In order to pass the course the student should be able to
- formulate simple and multiple regression models;
- give an account of the principle of least squares;
- carry out tests of linear hypothesis;
- perform validation of a regression model;
- select the important explanatory variables;
- use R for analysing real data sets;
- be able to interpret the results in practical examples.
Content
Simple linear regression. Multiple linear regression. Variable selection. F-tests. Least-squares estimation. Collinearity. Residual analysis. Nonlinear regression. R commands.
Instruction
Lectures and computer sessions
Assessment
Written examination at the end of the course. Compulsory assignments during the course.