TMA4267 Linear statistical models
Course information
| Reference group: | |||
|---|---|---|---|
| Markus B. Urfjell | markusu [at] stud [dot] ntnu [dot] no | MTFYMA | |
| Norunn Ahdell Wankel | norunnaw [at] stud [dot] ntnu [dot] no | MTFYMA | |
| Kristian A. Ruud | kristaru [at] stud [dot] ntnu [dot] no | MTFYMA | |
| Ebenezer Afrifa-Yamoah | ebenezea [at] stud [dot] ntnu [dot] no | MSMAT | |
| Solveig Fosdal | solvefos [at] stud [dot] ntnu [dot] no | MLREAL |
| Lecturer: | Mette Langaas, Mette [dot] Langaas [at] math [dot] ntnu [dot] no |
|---|---|
| Room 1236, 12.etg, Sentralbygg 2, Gløshaugen | |
| Office hours: Tuesdays and Thursdays after the lecture, that is, 16.00-17.00. |
| Teaching assistant | Jacob Skauvold, skauvold [at] math [dot] ntnu [dot] no |
|---|---|
| Room 1026, 10. etg, Sentralbygg 2, Gløshaugen | |
| Office hours: Thursdays 13.15-14.00 (before the lecture). |
Planned lectures and exercises: Time schedule
Learning outcome, Knowledge
- The student has strong theoretical knowledge about the most popular statistical models and methods that are used in science and technology, with emphasis on regression-type statistical models.
- The statistical properties of the multivariate normaldistribution are well known to the student, and the student is familiar with the role of the multivariate normal distribution within linear statistical models.
Learning outcome, Skills
- The student knows how to design an experiment and
- how to collect informative data of high quality to study a phenomenon of interest.
- Subsequently, the student is able to choose a suitable statistical model,
- apply sound statistical methods, and
- perform the analyses using statistical software.
- The student knows how to present the results from the statistical analyses, and how to draw conclusions about the phenomenon under study.