Course content

Point estimation, interval estimation and hypothesis testing for one- and two-sample normal data based on t, chi square and F distributions. Hypothesis testing in binomial models. Simple linear regression and analysis of variance for normal data. Goodness of fit and non-parametric tests. Use of statistical software.

Learning outcome

1. Knowledge. The student has a good knowledge about point estimation, confidence intervals and hypothesis testing, inference for one- and two-sample normal and for binomial models. The student also has a good knowledge about simple linear regression, analysis of variance and some nonparametric tests. 2. Skills. The student can, based on an existing data set, choose a suitable statistical model, apply sound statistical methods, and perform the analyses using statistical software. The student can present, interpret and communicate the results from the statistical analyses, and knows which conclusions can be drawn from the analyses, and what are the caveats. The student is able to discuss more complicated situations. The student can handle and analyze collected data using statistical software.

Learning methods and activities

Lectures and compulsory exercises. Written final examination is the basis for the grade awarded in the course. Parts of the teaching may be given in English.

Compulsory assignments

• Exercises

Recommended previous knowledge

ST1101 Probability and Statistics, MA1101 Basic calculus 1.

Course materials

Will be announced at the start of the course.

Credit reductions