G. Anichini Calcolo Vol. 4, Elementi di Calcolo delle Probabilit a e di
Inferenza Statistica, - Pitagora - Bologna - 1996.
2. D. Freedman - R. Pisani - R. Purves Statistica McGraw-Hill Libri Italia,
1998
3. I. Guttman - S.S. Wilks - J. Stuart Hunter Introductory engineering sta-
tistics, Wiley, John & Sons, 1982
4. M.R. Spiegel - J. Schiller - R.A. Scrinivasan Probabilit a e statistica, McGraw-
Hill Libri Italia, Collana Schaum, 2000
Prerequisites
Calculus and linear algebra
Teaching Methods
Lecture notes and exercises
Type of Assessment
written and oral exam
Course program
Elements of descriptive statistics: average; mode; range; median; and standard deviation; variance; percentiles; histograms. Elements of probability: Events, definition and rules of
probability, elements of combinatorics, probability conditioned
Bayes rule, stochastic independence. Random variables: discrete and continuous random variables, distributions,
the most common distribution functions (binomial, hypergeometric, Poisson,
...), Expected value, variance, covariance. Tools for estimating probability to (inequality Cebicev, ...); two or more random variables, functions of
random variables. Asymptotic theorems in the Calculus of Probability. Elements of sampling: simple random sampling from finite or infinite population
lations, sample mean and variance, the risk of consumers
tor and producer's risk. Operating curves. Basics
Inference (basics of point estimation, interval estimation, verifies hypotheses,
Bayesian estimation).