Applied Statistics

The course includes chi-squared tests (test for probabilities in multinomial models, model test with known and unknown parameters, test for homogeneity, test for independence) regression analysis, design of experiments (including analysis of variance and 2^k experiments), generalised linear models, transformations for normal approximations, variance stabilising transformations, non-parametric tests, approximations for mean and variance (including for estimators implicitly defined by an equation), combination of estimators, combination of tests, multiple testing (including Bonferroni correction), simulation tests and bootstrapping.

The objective of the course is to give the students a solid foundation in a broad variety of important statistical methods that can be used in technology, industry and biomodelling. In addition the students shall be capable of planning collection of data and to use statistical software for analysing data. The course is primarily for students in the two study programs Mathematics and statistics and Biomathematics.

Lectures and compulsory exercises. The final grade is a weighted sum based on both the written final exam (80%) and on a grade in the project (20%).

Retake of examination may be given as an oral examination.