Course content

The course builds upon the bachelor course in statistics (SØK1004) and provides students with the necessary skills for analyzing and interpreting data, both in the univariate and in the multivariate case. Students will learn to distinguish random variation from systematic variation and causality from correlation. The course will therefore briefly revise core statistical concepts used to describe data, and then emphasize estimation of simple ad multiple linear regression models via ordinary least squares. Particular emphasis will be posed on developing student competence in the use of statistical techniques and in the critical evaluation of simple empirical analysis.

Learning outcome

Knowledge:
You learn
- to define basic concepts underpinning data analysis, such as mean, variance, and hypothesis testing
- to define and derive the Ordinary least squares estimator (OLS)
- to present the basic assumptions underlying the OLS estimator
- to evaluate the credibility of causal claims in simple empirical applications

Skills:
You should
- be able to obtain summary statistics, tests and regression estimates
- be able to interpret summary statistics and basic regression results
- be able to criticize and evaluate simple empirical applications
- be able to write simple statistical programs with a statistical and econometric software

General competence:
You should
- describe data and economic relationships based on data
- distinguish correlation from causation
- acquire basic programming skills
- develop a reflective and critical approach to the practice of data analysis in economics

Learning methods and activities

2 hours of lectures every week, and 2 hours of practical assignments every other week.
The course has compulsory activity that will be announced at the beginning of the term.

Compulsory assignments

• Compulsory aktivity

Recommended previous knowledge

SØK1004

Required previous knowledge

None

Course materials

Announced at the beginning of the term

Credit reductions