Mandatory course within the Masterprogramme.
The course covers probability theory, such as random variables, probability distribution, expected values, independent samples, the central limit theorem, the law of large numbers, and consistency. Estimation of the population mean, hypothesis testing, and confidence intervals are also discussed. The course then discusses the linear regression model and how it can be applied. The regression model is also discussed using matrix algebra. The course further discus hypothesis tests and confidence intervals for both simple and multiple regressions. Different types of typical problems for the linear model, such as non-linear functions, omitted and irrelevant variables, simultaneity, measurement errors and heteroscedasticity are analysed.
This is a 7.5 credit course.
Course material will be available through the learning platform Athena during the course.
Instruction is given in the form of lectures and computer experiments. The language of instruction is English.
The course is examined on the basis of a written examination. Students may be awarded examination creditsduring the course through voluntary partial examination.
Examiner and Course director: Peter Skogman Thoursie.
ScheduleThe schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course.
Course literatureNote that the course literature can be changed up to two months before the start of the course.
Bruce E. Hansen, INTRODUCTION TO ECONOMETRICS, University of Wisconsin, Department of Economics. Open source. (can be downloaded at link in title)
Bruce E. Hansen, ECONOMETRICS, University of Wisconsin, Department of Economics (can be downloaded at link in title)
Stock & Watson, Introduction to Econometrics. Latest edition.