41301 - Statistical Inference

Academic Year 2019/2020

  • Docente: Patrizia Agati
  • Credits: 10
  • SSD: SECS-S/01
  • Language: Italian
  • Moduli: Patrizia Agati (Modulo 1) Paola Monari (Modulo 2)
  • Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
  • Campus: Bologna
  • Corso: First cycle degree programme (L) in Statistical Sciences (cod. 8873)

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