Attendance

Learning goals Introduction to problems and methods of Statistical decision theory and to its main approaches (Bayesian and frequentist). Students acquire the ability: - to formalize statistical problems as decision problems, - to compare different solutions - to apply decisional methods to real data Knowledge and understanding knowledge and understanding of: - general decision problems - statistical problems as decision problems - different approaches to statistical decision problems (Bayesian and frequentist) Applying knowledge and understanding At the end of the course students are able to: - formalize statistical problems as decision problems - apply and compare different decisional method to the most important models - apply decision theory to new models - interpret the results of their analysis Making judgements Students develop judgement skills by: - applying and comparing different decisional methods to a wide range of statistical models - interpreting the results from the use of alternative decision methods on real data Communication skills Students develop communication skills by: - solving and presenting problems in written and oral form - group activity Learning skills The comparative-analytical methodology used in the course provides students with a learning capacity that is an important basis to approach following courses in the statistical area of the master program and of more advanced programs (PhD in Statistics)."