course-details-portlet

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- og 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. The lectures may be given in English.

Compulsory assignments

  • Project

Further on evaluation

The re-sit exam may be changed to an oral exam. If the course is taught in English, the exam may be given only in English.

Specific conditions

Compulsory activities from previous semester may be approved by the department.

Course materials

James, G., Witten, D., Hastie, T., Tibshirani, R. "An Introduction to Statistical Learning with Applications in R", Springer. Additional literature will be announced at the start of the course.

Credit reductions

Course code Reduction From To
BBAN4001 7.5 AUTUMN 2020
Facts

Version: 1
Credits:  7.5 SP
Study level: Second degree level

Coursework

Term no.: 1
Teaching semester:  SPRING 2023

Language of instruction: English, Norwegian

Location: Trondheim

Subject area(s)
  • Statistics
Contact information
Course coordinator: Lecturer(s):

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.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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