41301 - Statistical Inference

Academic Year 2021/2022

  • Docente: Patrizia Agati
  • Credits: 10
  • SSD: SECS-S/01
  • Language: Italian
  • Teaching Mode: Traditional lectures
  • 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

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

Likelihood function

Point estimation: estimators and their properties; maximum likelihood method

Interval estimation

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

Parametric and distribution-free tests for means, proportions, variances, distributions

Readings/Bibliography

Lecture notes and slides.

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 and tutorials

Assessment methods

Written and oral exam (both mandatory)

Teaching tools

Blackboard and slides

Office hours

See the website of Patrizia Agati

SDGs

Quality education

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.