Application deadline

PhD students in science at UiT The Arctic University of Norway register for class and exam in Studentweb by September 1st for autumn semester and February 1st for spring semester.

Other applicants: Application deadline is June 1st for autumn semester and December 1st for spring semester. Application code 9301 in Søknadsweb (Applicationweb). Course code: STA-8002. Remember to write the course code in the extra information field.

Type of course

Admission requirements

PhD students or holders of a Norwegian master´s degree in Sceince of five years or 3+ 2 years (or equivalent) may apply. In your educational background you need statistical courses of at least 30 ECTS credits which includes a thorough discussion of statistical methods and principles.

PhD students from other universities must upload a document from their home institution stating that they are registered PhD students. This group of applicants does not have to prove English proficiency and are exempt from semester fee.

Holders of a Master´s degree must upload a Master´s Diploma with Diploma Supplement / English translation of the diploma. Applicants from listed countries must document proficiency in English. For more information on accepted English proficiency tests and scores, as well as exemptions from the English proficiency tests, please see the following document: https://uit.no/Content/254419/PhD_EnglishProficiency_100913.pdfhttps://uit.no/Content/254419/PhD_EnglishProficiency_100913.pdf

Proficiency in english - PhD level studies

PhD students at UiT The Arctic University of Norway register for the course through StudentWeb.

External applicants apply for admission through SøknadsWeb.

All external applicants have to attach a confirmation of their status as a PhD student from their home institution. Students who hold a Master of Science degree, but are not yet enrolled as a PhD-student have to attach a copy of their master's degree diploma. These students are also required to pay the semester fee.

More information regarding PhD courses at the Faculty of Science and Technology is found here.

Course content

Recommended prerequisites

Objectives of the course

• obtain a thorough introduction to the multivariate normal distribution, as well as estimation of its parameters.
• obtain solid understanding of various areas in multivariable statistical analysis, such as the classification problem, testing of general linear hypotheses, principal component analysis, factor analysis and various regression techniques.
• be able to use these concepts to solve concrete problems.

Language of instruction and examination

Teaching methods

Assessment

Oral exam (70%) and approved mandatory homework sets (30%).

Assessment scale: Letter grades A-F.

Coursework requirements
Oral presentation and mandatory homework set. A passing grade is required on the mandatory homework sets for permission to take the exam.