000143R - DATA SCIENCE FOR ECONOMICS

courses

ID:

000143R

Duration (hours):

72

CFU:

SSD:

STATISTICA ECONOMICA

Located in:

PESCARA

Url:

Course Details:

ECONOMICS AND BUSINESS ANALYTICS/CORSO GENERICO Year: 1

Year:

2025

Course Catalogue:

https://unich.coursecatalogue.cineca.it/af/2025?co...

Date/time interval

Secondo Semestre (11/02/2026 - 18/05/2026)

Course Objectives

The course of data science for economics aims to contribute to the student's learning process by providing methodologies for quantitative analyses that are useful for economic and business decisions. In particular, these learning objectives can be associated with the following expected learning outcomes: Knowledge and understanding The course aims to provide the basic methodological and application knowledge of data science. Furthermore, we want to provide useful tools for the statistical analysis of certain types of economic and business data. Finally, great attention will be given to the open source statistical package R. Applying knowledge and understanding At the end of the course, the student will also be able to analyze databases, including large ones, with modern statistical techniques, with the help of case studies carried out with the statistical software R. The acquired knowledge will allow him/her to critically interpret the economic and / or business dynamics.

Course Prerequisites

The knowledge of basic statistics is requested.

Teaching Methods

Lectures. R practice and exercises.

Assessment Methods

Knowledge and understanding The verification of the learning outcomes will be carried out through a written and oral examination. The written exam will cover the whole program with particular attention to the use of R software. Students will also have to prepare and discuss some statistical analyses, carried out with R, concerning real case studies (data sets can be found on the internet ). These documents must be sent to the Professor at least one week before the exam date. The score of the exam is assigned by a vote expressed in 30. Applying knowledge and understanding During the exam and the development of the applied work, students'ability to apply the knowledge of data science models is verified to be able to face concrete analysis situations.

Texts

Course slides. James G, Witten D, Hastie T, Tibshirani R (2021). An Introduction to Statistical Learning with Applications in R. Springer. Further readings: Giudici P, Figini S (2009). Applied Data Mining for Business and Industry. Wiley Ledolter J. (2013). Data Mining and Business Analytics With R. Wiley Shmueli G, Bruce PC, Yahav I, Patel NR, Lichtendahl KC, Jr. (2018). Data Mining for Business Analytics. Wiley

1. Introduction to R statistical software. Explorative analysis with R. 2.Statistical methods for the analysis of economic data: 2.1 Multiple linear regression with R. 2.2 Logistic regression model with R. 2.3 Decision trees with R. 2.4 Principal Component Analysis with R. 2.5 Multiple linear regression for spatial data with R.

Course Language

ITALIAN

More information

E-mail: paolo.postiglione@unich.it.For further details and for downloading the slides: fad.unich.it, page of Data Science per l'Economia. In the first semester the Professor meets students only by appointment (paolo.postiglione@unich.it). In the second semester, the office hours for students is scheduled for Thursday from 14:00 to 16:00, green stair, floor 1, Viale Pindaro, 42, Room n.33.