Learning outcomes of the course unit
The course provides the elements of probability theory useful for physical applications. The main emphasis is on stochastic processes (Markov chains and diffusion processes).
Prerequisites
Calculus
Course contents summary
Events and probability spaces, conditional probability, independence, Bayes' formula. Random variables, expectation and variance. Probability distribution and density. Functions of a random variable.
Several random variables, independence, covariance.
Markov chains
The law of large numbers
Recommended readings
Y.A.Rozanov, Probability theory: a concise course, Dover, 1969
Teaching methods
The course consists in a total of 32 hours of activities, mainly formal lectures, with some practice on the use of computer programs to generate and analyse random processes.
NAME OF LECTURER
CICUTA Giovanni
ACADEMIC YEAR: 2009/2010
YEAR OF STUDY: 3
SEMESTER: Second semester
NUMBER OF CREDITS: 4
CONTACT HOURS: 32
