Docente/Teacher

prof. Ruggero BELLIO

Crediti/Credits

6 CFU

Lingua/Language

Inglese/English

Obiettivi formativi specifici/Objectives

The course focuses on statistical methods for data analysis. Basic elements of statistical modelling will be provided, with emphasis on regression models and multivariate data analysis. Part of the course will take place in the computer lab, with use of the R statistical software.

Competenze acquisite/Acquired skills

- Knowledge of statistical methods for data analysis.
- Ability of applying the methods using the R statistical software.

Programma/Lectures and exercises (topics and specific content)

Basic concepts: introduction; data analysis and statistical models (8 hours).
Elements of statistical inference: summary of some basic concepts of statistical inference; some elements of maximum likelihood estimation and Bayesian methods (8 hours).
The R software:Basics; Programming in R; Usage for simple data analyses (10 hours).
Resampling methods: simulation methods; permutation tests and bootstrap methods (6 hours).
Regression models: simple linear regression; multiple linear regression; logistic regression; applications with R. (12 hours).
Further regression methods: analysis of complex data; introduction to time series analysis (6 hours).
Multivariate analysis: regression trees; dimension reduction techniques; classification methods; applications with R. (10 hours).

Bibliografia/References

- J. Maindonald, W.J. Braun: Data Analysis and Graphics Using R – An Example-Based Approach (Third Edition); Cambridge University Press, 2010 (Main text)
- J. Faraway: Linear Models with R (Second Edition); Chapman & Hall/CRC, 2014 (Supplementary text)
- B. Everitt, T. Hothorn: An Introduction to Applied Multivariate Analysis with R. Springer, 2011 (Supplementary text)

Modalità d'esame/Type of exam

Written and oral

Additional material and information available at the course web page