Statistical Experimental Design/
Number of credits: 6 hp
Examiner: Martin Singull
Course literature: Montgomery, D.C.: Design and Analysis of Experiments.
Course contents: Single-factor (including random effects model), two-factor and multifactor experiments in theory and practice. Randomized blocks, Latin squares and related designs. Complete 2^k factorial designs and fractional factorial designs. Construction of factorial designs. Response surface methods. Analysis of variance. Pairwise and multiple comparisons. Guidelines for designing experiments. Transformation of data. Power calculations. Nonparametric methods; sign test, Wilcoxon's tests, Kruskal-Wallis test, Friedmann's test. Fisher's exact test. Generalized linear models; logistic regression, poisson regression. Analysis of data by using statistical software.
Organisation: Lectures and example classes.
Examination: Written examination, computer exercises and hand in excersises.
Prerequisites: A first course in probability and statistics.
Last updated: 2022-11-15