


Politecnico di Torino  
Academic Year 2007/08  
03BXTGA Probability and statistics 

Master of sciencelevel of the Bologna process in Electrical Engineering  Torino 





Objectives of the course
Introducing modern statistical methodologies and their software implementation.

Expected skills
Ability to perform statistical analysis of experimental data on solid grounds

Prerequisites
Basic knowledge of analysis and geometry, up to numerical series and double integrals

Syllabus
Tables and graphs.
Measures of location and variability. Probability spaces. Uniform probabilities. Conditional probability and Bayes theorem. Random variables. Conditional distributions. Expected value, variance and covariance. Dicrete and continuous special distributions. Poisson process. Central limit theorem. Sampling distributions. Maximum likelihood. Confidence intervals. Simple linear regression. Outline of multiple regression. Exponential and Weibull distribution in reliability. System reliability. 
Laboratories and/or exercises
For each topic, there will be exercise sessions in the traditional 'blackboard' format.
Then, there will be four or more lab sessions on the software R, probaility in R, Programming in R, Linear models in R. 
Bibliography
Textbook is
Sheldon Ross, Probability and Statistics for Engineering and the Sciences. Apogeo 2003 ISBN: 8873038972 
Revisions / Exam
The exam is written: two exercises in probability and statistics plus at least one exercise with R (only passive knowledge required).

