Commission: R. Johnson, R. Fabbri, C. Franchetti, M. Marini, P. Pera
Office hours Monday and Tuesday 12:00-14:00
Type of Assessment
Written and oral exams
Course program
Elements of probability theory: events, probability spaces, random variables, expected value, variance. Gaussian variables, Poisson variables, binomial variables and others. Conditional probability, theorem of Bayes, independent events and random variables, Chebyshev's inequality, law of large numbers, central limit theorem.
Introduction to measure theory: Lebesgue measure, Lebesgue integral, abstract measures and probability measures.
Elements of statistics: sampling, confidence intervals, tests of hypothesis and test statistics, consistent estimators, unbiased estimators, estimators of the mean and the variance, Student's T distribution and the chi^2 distribution, test of goodness of fit, covariance and correlation, regression.