Course - Statistical Learning - TMA4268
TMA4268 - Statistical Learning
About
Examination arrangement
Examination arrangement: School exam
Grade: Letter grades
| Evaluation | Weighting | Duration | Grade deviation | Examination aids |
|---|---|---|---|---|
| School exam | 100/100 | 4 hours | G |
Course content
Statistical learning, multiple linear regression, classification, resampling methods, modell selection/regularization, non-linearity, tree-based methods, neural networks.
Learning outcome
1. Knowledge. The student has knowledge about the most popular statistical models and methods that are used for prediction in science and technology, with emphasis on regression- of classification-type statistical models.
2. Skills. The student can, based on an existing data set, choose a suitable statistical model, apply sound statistical methods, and perform the analyses using statistical software. The student can present, interpret and communicate the results from the statistical analyses, and knows which conclusions can be drawn from the analyses, and what are the caveats.
Learning methods and activities
Lectures, exercises and compulsory works (projects). The assessment is a final written examination (100%), whereas two projects need to be completed as compulsory activities, where at least 60% of the points must be reached to be admitted to the exam.
Compulsory assignments
- Project
Further on evaluation
The retake exam may be changed to an oral exam. The retake exam is in August.
Recommended previous knowledge
The course is based on TMA4240/4245 Statistics, or equivalent. Good understanding of linear algebra (matrix methods) and optimization.
The student will get maximum output from the course when taken together with TMA4267 and TMA4315 (either previous semester or in combination).
Course materials
The course material will be communicated at the beginning of the semester.
Credit reductions
| Course code | Reduction | From | To |
|---|---|---|---|
| BBAN4001 | 7.5 | AUTUMN 2020 | |
| TIØ4557 | 2.0 | AUTUMN 2023 |
Version: 1
Credits:
7.5 SP
Study level: Second degree level
Term no.: 1
Teaching semester: SPRING 2025
Language of instruction: English
Location: Trondheim
- Statistics
Department with academic responsibility
Department of Mathematical Sciences
Examination
Examination arrangement: School exam
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
- Spring ORD School exam 100/100 G INSPERA
-
Room Building Number of candidates - Summer UTS School exam 100/100 G INSPERA
-
Room Building Number of candidates
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"