Advanced Dataanalysis and Statistical Modelling

• analyze different type of data using the R program
• analyze variation in data
• identify important sources of variation
• asses the importance of different sources of variation by use of a statistical model
• present assumptions, method, results and interpretation of a statistical analysis
• pose, delimit and carry out a project within the framework of the course
• decide which model(s) are useful for analysing a given data set
• apply and understand likelihood based methods
• statistical model building

Likelihood methods and principels, general linear models, generalized linear models, mixed effects models, and generalized mixed effect models

02402/02403/02418/02409, Prerequisites in basic statistics and likelihood theory or multivariate statistics.

Lectures, exercises and student team work