41301 - Statistical Inference

Course Unit Page

Academic Year 2019/2020

Learning outcomes

By the end of the course, the student should know the main topics in statistical inference. Specifically, the student should be able to: 1- derive an estimator and its properties; 2- use estimating methods; 3- define and verify parametric and non parametric statistical hypothesis in simple contexts; 4- build confidence intervals.

Course contents

Likelihood function

Random sampling. Sample space, sample random variables and sample distributions

Point estimation: estimators and their properties; maximum likelihood method

Interval estimation

Hypothesis testing: Fisher significance tests and Neyman-Pearson hypothesis tests

Test-statistics for means, proportions, variances, distributions

Distribution-free tests

Readings/Bibliography

Teacher's notes

G. Cicchitelli, Statistica: principi e metodi, Pearson, Milano, 2012

A. Montanari, P. Agati, D.G.Calo, Statistica con esercizi commentati e risolti, CEA, 1998 

Teaching methods

Lectures

Classroom exercises

 

Assessment methods

Written exam (4-5 exercises)

Oral exam

Teaching tools

Blackboard; PC; videoprojector

Office hours

See the website of Patrizia Agati

See the website of Paola Monari