Probability and data science

MAT12 Probability and data science

Autumn 2025

Spring 2025
  • Topics

    The course deals with probability theory and methods for statistical inference and is preparing students for future studies in business analytics, econometrics and statistics. The statistical software R is used in the course.

    - Stochastic variables, probability distributions, one- and multivariate

    - Transformations of variables; 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

    - Sample distributions

    - Estimation: The maximum likelihood principle, consistency and efficiency

    - Hypothesis testing: The likelihood ratio method

    - Bayesian methods

  • Learning outcome

    Knowledge

    After completing the course the student

    • knows the theory foundation for the statistical methods studied at the compulsory courses in statistics
    • has knowledge to solve statistical problems which does not have a worked out solution in introductory text books in economic statistics

    Skills

    After completing the course the student can

    • formulate a stochastic model based on a given decision problem
    • fit this model to a data set
    • evaluate the uncertainty in this fit

    General competence

    After completing the course the student is prepared to

    • a faster progression in quantitative courses in later master studies
    • read more advanced articles in economic journals, particularly with respect to econometrics

  • Teaching

    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

    Corresponds to MAT013

  • Compulsory Activity

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

  • Assessment

    6 hours digital school exam where focus is on both theory and data analysis with R.

    An assessment will not be organised in the the non-teaching semester (spring).

  • Grading Scale

    A - F

  • Computer tools

    R

  • Literature

    • (HT) Hogg, Tanis and Zimmerman: Probability and statistical inference 10ed, Pearson, 2024
    • Other material which will be available in Canvas

  • Permitted Support Material

    Calculator

    One bilingual dictionary (Category I)

    All in accordance with Supplementary provisions to the Regulations for Full-time Study Programmes at the Norwegian School of Economics Ch.4 Permitted support material https://www.nhh.no/en/for-students/regulations/https://www.nhh.no/en/for-students/regulations/and https://www.nhh.no/en/for-students/examinations/examination-support-materials/https://www.nhh.no/en/for-students/examinations/examination-support-materials/

Overview

ECTS Credits
7.5
Teaching language
Norsk

Course responsible

Professor Jonas Andersson, Department of Business and Management Science.