spring 2023
HIF-3082 Quantitative Methods in Linguistics - 10 ECTS

Application deadline

Applicants from countries within EU/EEA: 1 June for courses offered in the autumn semester and 1 December for courses offered in the spring semester.

Exchange students and Fulbright students: 15 April for courses offered in the autumn semester and 1 October for courses offered in the spring semester.

Type of course

This course is mandatory for students in the MA programme in English Acquisition and Multilingualism, and elective for students in the MA programme in Theoretical Linguistics. This course may be taken as a single course by students who qualify for admission to the MA programme in Theoretical Linguistics and/or a MA programme in linguistics in general (Russian, Spanish etc.).

Admission requirements

A bachelor's Degree (180 ECTS), or equivalent qualification, in a language or linguistics, or a degree combining linguistics and literature (minimum 80 ECTS in linguistics/language/literature, of which minimum 60 ECTS must be in linguistics and/or language). 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.

Application code: 9371 - Enkeltemner på masternivå (Nordic applicants).

Course content

This course introduces students to some of the major tools required in the organization and understanding of quantitative linguistic data. This will include: general analytic method, probabilistic logic, statistics, and the use of the programming language R. It is appropriate for students who are interested in data gathered either experimentally or from corpora.

Objectives of the course

The students have the following learning outcomes:


By the end of the course the student has a basic knowledge and understanding of the following areas:

  • General Logic and Inference
  • Basic Probability Theory
  • Modelling and Statistical Tests
  • The Programming Language R for Statistical Analysis


In practical terms, the student has acquired the following connected skills:

  • How to gather and organize data either experimentally or from corpora.
  • How to model complex data with appropriate choice of statistical model.
  • How to test statistical models with the appropriate tests.
  • How to use R to organize and explore patterns in the data, and run the standard statistical tests required in reporting scientific research.

Language of instruction and examination

Language of instruction and examination: English.

Teaching methods

Lectures, seminars/exercises and discussions.

Quality assurance: All courses undergo a halfway evaluation once in a 2-year period at the master's level. The Programme Board determines which programme options will be evaluated per year, and which courses will be evaluated by the students and the teacher per year.

Information to incoming exchange students

This course is open for exchange students who fulfill the admission requirements (please see the "Admission requirements" section). The course should be taken as a part of a course package.



Examination: Date: Duration: Grade scale:
Assignment Innlevering: 31.05.2023 kl. 14:00 1 Semesters A–E, fail F
UiT Exams homepage

More info about the assignment

An assignment of approximately 15 pages on a topic chosen by the student in consultation with the instructor. The student will work on the term paper throughout the semester under supervision of the instructor and deliver it on the assigned date. The term paper will be written in English.

Re-sit examination

A resit exam is arranged for students who have not passed the last ordinary exam in this course. In the event of a re-sit examination, the student is allowed to submit a revised version of his/her term paper within a given deadline.
  • About the course
  • Campus: Tromsø |
  • ECTS: 10
  • Course code: HIF-3082
  • Tidligere år og semester for dette emnet