37684 - Statistics Crash Course

Academic Year 2018/2019

  • 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

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