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  1. Courses

ECBA014 - STATISTICAL LEARNING

courses
ID:
ECBA014
Duration (hours):
48
CFU:
6
SSD:
STATISTICA
Located in:
PESCARA
Url:
Course Details:
ECONOMICS AND BUSINESS ANALYTICS/CORSO GENERICO Year: 2
Year:
2025
Course Catalogue:
https://unich.coursecatalogue.cineca.it/af/2025?co...
  • Overview
  • Syllabus
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Overview

Date/time interval

Primo Semestre (17/09/2025 - 14/12/2025)

Syllabus

Course Objectives

The course provides knowledge about the analysis of compex data. The course aims to provide the student with the tools to
extract relevant information from large amounts of data, with particular attention to statistical learning (statistical learning) both in a predictive
and non-supervised context (supervised and non-supervised learning).

LEARNING OUTCOMES
The course aims at completing student's training with notions and tools useful to deepen the aspects of multivariate statistical analysis. The training will then be completed and enriched by the following skills:

Knowledge and understanding / Applying knowledge and understanding
- Knowledge of statistical concepts for multivariate analysis and related specialized terminology
- Ability to apply the principles of statistical reasoning in the preparation and interpretation of company reports
- Ability to use R and MATLAB software for statistical analysis

Making judgements
- To learn the logical and statistical concepts that are indispensable for working independently in the research, selection and processing of
complex data .

Communication skills
- Learn the terminology and statistical techniques of multivariate analysis to communicate or correctly discuss the results of the analysis of
complex data

Course Prerequisites

Mathematics (calculus), linear algebra, matrices, and statistical inference (estimation and statistical test)

Teaching Methods

Frontal lectures as well as practical exercises with the use of the software R

Assessment Methods

The exam is mainly based on an oral discussion aiming at verifying the knowledge of the theoretical part of the topics covered in class. A discussion of a report prepared for the analysis of a data sets (chosen by the student) using the R software is also required. In the determination of the final grade the discussion of the report accounts only for a 30%.

Texts

- Slides and handouts for students not attending the course will be available from the professor

- Maindonald, Braun (2010) Data Analysis and Graphics Using R: An Example-Based Approach. 3rd edition, Cambridge University Press
- James, Witten, Hastie, Tibshirani (2013) An Introduction to Statistical Learning (with Applications in R), Springer-Verlag
- Kevin Murphy (2012) Machine learning : a probabilistic perspective, The MIT Press, Cambridge, Massachusetts, London, England
- Luìs Torgo (2011) Data Mining with R. Learning with case studies. CRC Press

Contents

The following topics are considered as important parts of the teaching
program for the fulfilment of the objectives: introduction to Statistical Learning, data visualization, regression and classification,
Non-supervised learning (principal component analysis, Clustering, procruste), Analysis if complex data (spatial data and social data mining)

Course Language


The course will be given in Italian. Slides and Textbooks are mainly inEnglish

More information

E-mail: luigi.ippoliti@unich.it

Students will be received on Mon and Wed between 15:00 and 16:00

Appointments can be fixed by e-mail.

Degrees

Degrees

ECONOMICS AND BUSINESS ANALYTICS 
Master’s Degree
2 years
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People

People

IPPOLITI Luigi
Gruppo 13/STAT-01 - STATISTICA
AREA MIN. 13 - Scienze economiche e statistiche
Settore STAT-01/A - Statistica
Docenti di ruolo di Ia fascia
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