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