Probability Random variables univariate and multivariate. Expectation of functions of randoma variables. Probability models discrete and continuous. Sampling and sampling distributions. Point estimation. Interval estimation. Theory of testing hypotheses. Two samples problems. Linear statistical models (analysis of variance, regression and analysis of covariance). Bayesian statistical inference. Nonparametric statistical inference. Statistical decision theory.
Barnett V. (1999). Comparative Statistical Inference (3a ed.). J. Wiley.
DeGroot M.H., Schervish m. j. (2012). Probability and Statistics (4a ed.). Addison-Wesley.
Keener R.W. (2010). Theoretical Statistics, Springer.
Mood, A.M., Graybill, F.A., Boes, D.C.(1988). 'Introduzione alla statistica'. McGraw-Hill.
Olive D.J. (2014). Statistical Theory and Inference, Springer.
Rohatgi V.K., Salek A.K. (2001). An Introduction to Probability and Statistics (2a ed.). J. Wiley.
Learning Objectives
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Prerequisites
Intermediate knowledge of Differential Calculus.
Linear Algebra
Teaching Methods
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Further information
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Type of Assessment
Written + Oral Exam
Course program
Probability Random variables univariate and multivariate. Expectation of functions of randoma variables. Probability models discrete and continuous. Sampling and sampling distributions. Point estimation. Interval estimation. Theory of testing hypotheses. Two samples problems. Linear statistical models (analysis of variance, regression and analysis of covariance). Bayesian statistical inference. Statistical decision theory.