Statistical modelling: Theory and practice

• Formulate and apply the most common statistical models
• Perform model check and be able to evaluate the adequacy of statistical methods in specific applications
• Be able to interpret and present results from statistical analysis
• Have knowledge about estimation methods, in particular the principle of Maximum Likelihood
• Have knowledge about simulation based methods
• Have knowledge about Bayesian methods
• Be able to perform standard statistcial analysis using the statistical software R
• Recognize the possible use and potential of more advanced statistical methods
• Be able to present statistical findings for an audience without statistical background

The course will cover the most common methods in applied statistics, usually illustrated with case stories and the statistical software R. Also more theoretical issues are covered. A number of lectures will introduce more advanced topics and thus motivates for more advances courses at the Department.

02402/02403, Knowledge of statistical methods equivalent to course 02402/02403. Some additional knowledge of probability theory is an advantage.

Lectures and excercises (integrated) plus solution of a practical assignment.

The course is a link between the introductory course and more advanced course offered at the Department.