- 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)
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from Sep 17, 2024 to Dec 13, 2024
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
Statistical inductive reasoning. 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
Slides and additional resources will be uploaded on Virtuale (https://virtuale.unibo.it/)
Office hours
See the website of Patrizia Agati
SDGs
This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.