ID:
DAES04A
Duration (hours):
48
CFU:
6
SSD:
Statistica
Located in:
PESCARA
Url:
DATA ANALYTICS FOR ECONOMICS AND SOCIETY/CORSO GENERICO Year: 1
Year:
2026
Course Catalogue:
Overview
Date/time interval
Secondo Semestre (15/02/2027 - 31/05/2027)
Syllabus
Course Objectives
The course aims to achieve the overall objective of the study program, which is to train professional figures skilled in data management and analysis in all work contexts.
The course aims to provide students with the basic concepts of probability theory, such as events, sample spaces, conditional probability, Bayes' theorem, and probability distributions. It also aims to introduce the main discrete and continuous random variables, their distributions, and explain how to calculate and interpret parameters like mean, variance, and moments. The study of key probability theorems, such as the law of large numbers, the central limit theorem, and limit distributions, is also included. Finally, some probabilistic models are presented, aimed at describing random phenomena and analyzing real-world situations through probability.
By the end of the course, students will have gained both theoretical and practical knowledge of probability theory and key random variables. This knowledge, which is applicable across various economic, managerial, and social fields, will enable students to model real-world phenomena and conduct investigations, experiments, and data analysis.
To this end, the course aims to impart the following skills and knowledge:
KNOWLEDGE AND UNDERSTANDING CAPACITY
- basic concepts of probability theory;
- main probabilistic models (discrete and continuous) such as the binomial, Poisson, and normal random variables;
- expected value, variance, and, in general, moments of random variables;
- key probability theorems.
To achieve this, the course aims to convey the following specific skills and knowledge:
KNOWLEDGE AND UNDERSTANDING CAPACITY (applied)
- use mathematical tools to solve problems of a probabilistic and statistical nature;
- apply probability theorems and axioms, and use the main random variables;
- use statistical software to conduct data analysis and produce summary reports.
JUDGMENT AUTONOMY:
- independently identify the tools and probabilistic models to use in formalizing and analyzing a real-world phenomenon;
- present oral analytical and synthetic considerations on the fundamental aspects of the discipline;
- provide a critical assessment of the results of analyses and draw conclusions, including through interdisciplinary connections, that offer strategic insights and their socio-economic implications.
COMMUNICATION SKILLS:
- use statistical language pertinently;
- communicate the results of statistical analyses and the underlying logical reasoning, both in writing and orally, even in interdisciplinary contexts and in the presence of non-expert audiences.
LEARNING SKILLS:
- conduct individual and group research on specific aspects and topics of interest in various economic and social application domains.
The course aims to provide students with the basic concepts of probability theory, such as events, sample spaces, conditional probability, Bayes' theorem, and probability distributions. It also aims to introduce the main discrete and continuous random variables, their distributions, and explain how to calculate and interpret parameters like mean, variance, and moments. The study of key probability theorems, such as the law of large numbers, the central limit theorem, and limit distributions, is also included. Finally, some probabilistic models are presented, aimed at describing random phenomena and analyzing real-world situations through probability.
By the end of the course, students will have gained both theoretical and practical knowledge of probability theory and key random variables. This knowledge, which is applicable across various economic, managerial, and social fields, will enable students to model real-world phenomena and conduct investigations, experiments, and data analysis.
To this end, the course aims to impart the following skills and knowledge:
KNOWLEDGE AND UNDERSTANDING CAPACITY
- basic concepts of probability theory;
- main probabilistic models (discrete and continuous) such as the binomial, Poisson, and normal random variables;
- expected value, variance, and, in general, moments of random variables;
- key probability theorems.
To achieve this, the course aims to convey the following specific skills and knowledge:
KNOWLEDGE AND UNDERSTANDING CAPACITY (applied)
- use mathematical tools to solve problems of a probabilistic and statistical nature;
- apply probability theorems and axioms, and use the main random variables;
- use statistical software to conduct data analysis and produce summary reports.
JUDGMENT AUTONOMY:
- independently identify the tools and probabilistic models to use in formalizing and analyzing a real-world phenomenon;
- present oral analytical and synthetic considerations on the fundamental aspects of the discipline;
- provide a critical assessment of the results of analyses and draw conclusions, including through interdisciplinary connections, that offer strategic insights and their socio-economic implications.
COMMUNICATION SKILLS:
- use statistical language pertinently;
- communicate the results of statistical analyses and the underlying logical reasoning, both in writing and orally, even in interdisciplinary contexts and in the presence of non-expert audiences.
LEARNING SKILLS:
- conduct individual and group research on specific aspects and topics of interest in various economic and social application domains.
Course Prerequisites
Knowledge of mathematics.
Teaching Methods
Frontal lessons and exercises.
Assessment Methods
The learning assessment procedures consist of two parts: an oral exam, made of exercises and theoretical questions (open questions) on topics that cover the entire program of the course (probability and random variables); application of Statistical methodologies using the R software. Students will have to demonstrate that they are able to formalize a problem in quantitative terms, to select the appropriate indices and statistics for its solution and to provide an interpretation of the results obtained.
The grade is expressed in thirtieths. Students with disabilities, Specific Learning Disorders (SLDs), or other special educational needs may benefit from individualized arrangements during examinations, in compliance with current regulations and with the provisions set out in the University Service Charter (https://www.unich.it/sites/default/files/2024-02/carta_dei_servizi_0.pdf), subject to prior agreement with the course instructor. To request compensatory and dispensatory measures, students must contact the CON_TE_STO Service and follow the procedure indicated in the Service Charter.
Students are encouraged to contact the course instructor during the teaching period, or in any case well in advance of the examination date, in order to obtain information about the examination procedures and the measures that may be granted.
For guidance and information about the various services offered by the University, students may contact the Departmental Faculty Representative.
The grade is expressed in thirtieths. Students with disabilities, Specific Learning Disorders (SLDs), or other special educational needs may benefit from individualized arrangements during examinations, in compliance with current regulations and with the provisions set out in the University Service Charter (https://www.unich.it/sites/default/files/2024-02/carta_dei_servizi_0.pdf), subject to prior agreement with the course instructor. To request compensatory and dispensatory measures, students must contact the CON_TE_STO Service and follow the procedure indicated in the Service Charter.
Students are encouraged to contact the course instructor during the teaching period, or in any case well in advance of the examination date, in order to obtain information about the examination procedures and the measures that may be granted.
For guidance and information about the various services offered by the University, students may contact the Departmental Faculty Representative.
Texts
Notes provided by the teacher.
Suggested books:
Borra, S., Di Ciaccio A., Statistica, metodologie per le scienze economiche e sociali, third edition, McGraw-Hill, 2014.
Sheldon M. Ross, Probabilità e statistica per l'ingegneria e le scienze, fourth edition, Apogeo, 2023
Suggested books:
Borra, S., Di Ciaccio A., Statistica, metodologie per le scienze economiche e sociali, third edition, McGraw-Hill, 2014.
Sheldon M. Ross, Probabilità e statistica per l'ingegneria e le scienze, fourth edition, Apogeo, 2023
Contents
Introduction to the fundamentals of probability theory and the concept of random variable to lay the groundwork for the discussion of sampling and statistical inference. Concepts of expected value, variance, and association between variables. Main discrete and continuous random variables, multiple variables and joint probability distributions, functions of random variables, and probability theorems.
Course Language
Italian
More information
Additional material for exam preparation (slides, exercises, etc.) are available on the e-learning or FAD websites, respectively, https://elearning.unich.it/ and https://fad.unich.it/.
If Health Laws and University regulations allow teaching activities, teachers office hours’, and exams may take place online (in whole or in part).
For any further information and updates, please refer to the University website.
If Health Laws and University regulations allow teaching activities, teachers office hours’, and exams may take place online (in whole or in part).
For any further information and updates, please refer to the University website.
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DATA ANALYTICS FOR ECONOMICS AND SOCIETY
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