Data analysis

Learning objectives

The course has as its educational objective to introduce the student to the statistical study of business phenomena, through elementary and advanced statistical techniques, which have an immediate operational applicability in concrete operational contexts.
Therefore, the course, after having presented some random variables, will essentially develop on the applicability of statistical concepts in the research carried out by the teacher during his academic career.
Specific topics that will be covered will be quality assessment, job satisfaction and health literacy.

Expected learning outcomes

It is desirable that students acquire those statistical skills that will guide them in making sound business decisions.

Course content

Random variables and their properties.
The moment generating function.
The main random variables: the Bernoulli variable, the rectangular, Poisson, Gaussian, gamma and chi-squared.
Statistical techniques for the analysis of inequalities.
Statistical tools for evaluating customer satisfaction and job satisfaction.

Prerequisites

It is assumed that students already have a basic understanding of descriptive and inferential statistics topics.
Knowledge of some basic elements of mathematical analysis is also required.

Bibliography

Iezzi, D. (2024). From Data to Knowledge. Statistics for Decisions. Carrocci Editore

Franci A., Renzi P. (2021). Health inequalities and social-health policies – Conceptual models of the social determinants of health and their applications. Maggioli Editore

Handouts provided by the professor

Teaching methods and tools

The content of the lessons will be supported by slides presented during the course.
Students will be divided into groups and assigned specific topics that will provide guidelines for setting up research consistent with the educational objectives of the degree course.

Assessment methods and criteria

The learning assessment will take place through an oral interview, with particular reference to the topics covered in the course and the papers produced by the groups.