Empirical Methods

MET4 Empirical Methods

Spring 2020

  • Topics

    This course builds on and extends the methodology and key subjects from the first year. Students will be trained in the use of empirical analysis for decision making. Special emphasis is given to interpretation of economic and behavioural data. Students will learn to distinguish random variation from systematic variation and causality from correlation. Methodological issues are integrated with other economic subjects through examples and specific applications. While the main focus in the first year course in statistics is univariate analyses, this course also covers multivariate methods.


    The following topics are covered:


    1. Introduction to scientific methods in social sciences

    • Methodology
    • Qualitative vs quantitative analysis
    • Research ethics


    2. Descriptive statistics

    • Population and sample
    • Types of data and information
    • Central location, variance and co-variance


    3. Comparing two populations

    • Sampling distributions
    • Comparing two means
    • Comparing two variances
    • Comparing two proportions


    4. Comparing more than two groups

    • One-way analysis of variance
    • Two-way analysis of variance


    5. Chi-squared tests

    • Goodness-of-fit (more than two proportions)
    • Test for independence in a contingency table


    6. Non-parametric tests


    7. Regression analysis

    • Simple regression
    • Multiple regression: Modelling and residual analysis
    • Panel data
    • Categorical regression (logit and probit)


    8. Time series analyses and prognoses

  • Learning outcome

    Upon successful completion the students



    • Have an understanding of statistical methods used in economics and business administration



    • Are able to perform simple analytical calculations and empirical analysis of data they may encounter in graduate studies or business life
    • Have knowledge of statistical software


    General Competence

    • Have experience with project work and reporting of statistical analyses

  • Teaching

    Teaching consists of lectures and data labs. In the data labs students will work with exercises and cases from the textbook. Student will have to hand in an assignment to document competence in the use of statistical software and reporting of results.

  • Recommended prerequisites

    It is assumed that the students are in command of the contents of MET2 and MET3.

  • Required prerequisites

    It is assumed that the students are in command of the contents of MET2 and MET3.

  • Requirements for course approval

    Course approval is given when the hand-in assignment is accepted (approved/not approved).

  • Assessment

    The final grade is based on a written school exam (3 hours), which counts 70 %, and a take home exam (3 days, from 09:00 on day 1 until 14:00 on day 3), which counts 30 %. The take home exam is done in groups of 2-4 students.


    Examination questions are written in Norwegian and English both semesters and can be answered in both language in both semesters.


    The two exams elements can be taken independently, but it is recommended to take them within one term.

  • Grading Scale

    A-F for both assessment elements and the overall course grade.

  • Computer tools

    Excel and R

  • Literature

    Keller: Statistics for Management and Economics, 11th Edition (or earlier editions, including Managerial Statistics, 8th or 9th Edition). Cengage.


    Lecture notes.


    Parts of the curriculum are also covered in Jan Ubøe, Statistikk for økonomifag, which is used in MET2.


ECTS Credits
Teaching language
English (Autumn) and Norwegian (Spring).

Spring (Norwegian) and Autumn (English). Offered Spring 2020 (Norwegian).

Course responsible

Associate Professor Evelina Gavrilova-Zoutman, Department of Business and Management Science (Autumn).

Assistant Professor Håkon Otneim, Department of Business and Management Science (Spring).