37684 - Statistics Crash Course

Academic Year 2021/2022

  • Teaching Mode: Traditional lectures
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Economics and Economic Policy (cod. 8420)

Learning outcomes

Knowledge of elementary proabability theory and statistical tools (descriptive statistics and inference for normal and binomial models). The student should be able to solve simple practical problems

Course contents

Descriptive statistics: central measures, dispersion indicators and graphical representations

Multivariate statistics: independence, association and correlation.

Linear model and generalized linear model

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.


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.



<18 fail

18-23 pass

24-26 satisfactory

27-28 good

29-30 very good

30 e lode excellent

Teaching tools

Notes, exercises and slides

Office hours

See the website of Alessandro Baldi Antognini


Decent work and economic growth

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