Mathematical Statistics

MAT12 Mathematical Statistics

Autumn 2020

  • Topics

    - Stochastic variables. probability distributions, one- and multivariate

    - Transformations of variables and convolutions; moments

    - Special distributions: Normal, exponential, Gamma, Beta, t, F and chisquare.

    - Modes of convergence: in probability, in distribution; law of large numbers and the central limit theorem

    - Estimation: The maximum likelihood principle, consistency and efficiency

    - Hypothesis testing: The likelihood ratio method

    - Bayesian methods

  • Learning outcome


    After completing the course, the student knows the theory foundation for the statistical methods studied at the compulsory courses in statistics.


    After completing the course, the student can formulate a stochastic model and fit it to a data set. The student can also evaluate the uncertainty of the fitted model.

    General compentence

    After completing the course, the student is prepared for a faster progression in later master studies.

  • Teaching

    The course is given in the fall semester and has a scope of 7.5 ECTS. The teaching is given in the form of lectures, where both theory, examples and exercises is discussed.

  • Recommended prerequisites

    MAT10 Analyse og lineær algebra (Calculus and Linear Algebra)

  • Required prerequisites

    MET040/MET2 - Statistikk for økonomer (Statistics for Economists)

  • Credit reduction due to overlap

    Correspond to MAT013

  • Requirements for course approval

    A compulsory assignment must be passed in order to attend the written exam.

  • Assessment

    5 hours written exam

  • Grading Scale


  • Computer tools


  • Literature

    (HT) Hogg and Tanis: Probability and statistical inference 8ed, Prentice Hall, 2010 (7ed er også mulig å bruke)


ECTS Credits
Teaching language

Course responsible

Professor Jonas Andersson, Department of Business and Management Science.