Academic Year 2018/2019

  • Teaching Mode: Traditional lectures
  • Campus: Forli
  • Corso: First cycle degree programme (L) in Economics and business (cod. 9202)

Learning outcomes

At the end of the course students have the basic tools for analyzing and describing a set of data through graphical representations and numerical indexes. Moreover, the course aims at providing students with the main concepts of probability theory and inference.

Course contents

Part 1 – EXPLORATORY DATA ANALYSIS

Introduction. The data matrix. Type of variables. Frequency tables. Cumulative frequency distribution. Graphical representations. Summary statistics of location (mean, median, mode) and dispersion. Linear transformations. Two-way tables: joint, marginal and conditional frequencies. Association of two quantitative variables, covariance and correlation. Linear regression.

Part 2 – PROBABILITY

Random events, uncertainty, axioms of Probability, conditional probability and Bayes theorem. Discrete and continuous random variables, Central Limit theorem.

Part 3- STATISTICAL INFERENCE

Statistical models, population and sampling. Simple random samples and parametric inference. Parameters estimation and confidence intervals. Testing statistical hypotheses: normal and binomial models.

Readings/Bibliography

S. Borra e A. Di Ciaccio (2014) Statistica. Metodologie per le Scienze Economiche e Sociali (III ed.), McGraw-Hill Education.

Teaching methods

Traditional lectures and homework.

Assessment methods

Written examination. In some cases, after the written exam, the lecturer may require an oral exam as a further tool of assessment of the student's preparation.

Teaching tools

Notes, exercises and slides.

Office hours

See the website of Maroussa Zagoraiou