Statistics is a tool for analysing data in complex systems.
The Master’s degree program comprises a Master’s Thesis of 60 ECTS, 20 ECTS mandatory courses in computer-intensive statistics and multivariable statistical analysis, and four courses (40 ECTS) of electives or special curriculum.
Statisticians at the Department of mathematics and statistics are mainly focusing on imaging, climate research, medical statistics, ecology and machine learning. The Master’s Thesis, electives and special curriculum make it possible for students to specialize in these different areas
|Term||10 ects||10 ects||10 ects|
|First term (autumn)||
STA-3002 Multivariable Statistical Analysis
|Second term (spring)||
STA-3001 Computer-intensive Statistics
|Third term (autumn)||
STA-3900 Master’s Thesis in Statistics
|Fourth term (spring)|
For each programme at the University of Tromsø there are set targets for knowledge, skills and competences that a student should have reached by the end of studies.
On completion of the program, graduates will have the following attributes:
- have advanced knowledge of statistical concepts, principles and methods
- have a solid knowledge about fields close to statistics, especially within mathematics
- have sufficient knowledge of statistics to teach in senior high school
- have a solid knowledge of a concrete scientific problem issue and the statistical model that describes the problem
- can enter complicated problem issues, uncover structures and formulate precise problems, find suitable analytical and/or numerical solution methods, and interpret the solutions
- have good practical skills in at least one commonly used statistical programming tool.
- can cooperate, if necessary in a interdisciplinary way, with other specialists.
- can find precise and scientific formulations, in oral and written language, in Norwegian as well as in English
- can use existing literature in an active way to understand the work of other scientists, and as support to solve own mathematical problems.
- can use statistical methods in theory and practice, and make an independent judgment of the applicability of a statistical model for a given practical problem
- have a solid knowledge of a broad variety of methods and techniques for analysis and problem solving within statistics.
- have acquired good theoretical insight and ability to apply the theory for development of methods and techniques to solve problems.
- possesses the necessary qualifications for work within industry, technology, science, information technology, and schools.
- can apply knowledge within mathematics and statistics on problem issues within social and natural sciences.
- can do independent scientific work and formulate the contents of the work within the framework of the terminology of the field
- can make knowledge based judgments on general scientific issues and communicate these in public.
Admission to the programme in Statistics – master, requires a Bachelor’s degree (180 ECTS) in Statistics or Mathematics or another degree following a program of study of at least three years, or similar education approved in accordance with the Norwegian Universities Act section 3-4.
In addition, specialization in statistics/mathematics worth the equivalent of not less than 80 ECTS credits is required.
- Applicants who hold a bachelor’s degree or equivalent issued in Europe, Canada, USA, Australia and New Zealand: An average grade C as a minimum requirement,
- Applicants who hold a bachelor’s degree or equivalent issued in countries other than the above mentioned region/countries: An average grade B as a minimum requirement.
More information on formal admission requirements:
Applicants from Norway or Nordic countries:
- The application deadline for Norwegian and other Nordic applicants is April 15th for admission to the autumn semester and November 1st for admission to the spring semester.
Applicants from outside the Nordic countries:
- The application deadline for self-financing international applicants is December 1st for admission to the autumn semester.
- Online application, study code 2036.
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