82209 - Statistics Pass/Fail Test

Learning outcomes

At the end of the course, students have acquired knowledge of the main statistical techniques for exploratory data analysis and the fundamental concepts of inference from random samples. The learnt techniques cover graphical tools and summary measures for single and multiple variables, estimation and hypothesis testing for Gaussian and Binomial populations.

Course contents

Descriptive statistics: central measures, dispersion indicators and graphical representations

Basic probability theory: sample space and events, the axioms of probability theory, conditional probability and Bayes' Theorem. Random variables (discrete and continuous), expectation and variance. Independence and sequence of random variables: strong law of large numbers and central limit theorem.

Introduction to statistical inference: randomization and sampling. Statistical models and parameters.

Inferential statistics: Point Estimation, Confidence Intervals, Hypothesis Testing.

Readings/Bibliography

S. Borra e A. Di Ciaccio (2008) Statistica. Metodologie per le Scienze Economiche e Sociali (II ed.), McGraw-Hill.
G. Cicchitelli (2008) Statistica - Principi e Metodi, Pearson Education

Teaching methods

Lectures, problem classes, homework

Assessment methods

Written test.

Teaching tools

Notes, exercises and slides

Office hours

See the website of Alessandro Baldi Antognini

See the website of Linda Altieri