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## Subject: STATISTICAL MODELS FOR BUSINESS DECISIONS (A.A. 2023/2024)

### master degree course in ECONOMICS AND LAW FOR THE ORGANIZATIONS' SUSTAINABILITY

Course year 1 9 Unit Unico Statistics and Mathematics (lesson) TAF: Compulsory subjects, characteristic of the class SSD: SECS-S/01 CFU: 9 Teachers: Viviana DE GIORGI written final vote Italiano

### Overview

The course aims to provide the basic elements of descriptive statistics, probability, inference, with an introduction to multivariate statistics, in order to learn how to explore, organise, represent, and summarise data, and to understand how general characteristics of a phenomenon can be inferred from specific observations.

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### Course contents

General concepts. Phases of research. Data collection phase. Designing a questionnaire. Graphical representation. Data processing: mean values, statistical ratios, variability, concentration. Principles of probability. Statistical distributions. Point estimates. Interval estimates. Sample size determination. Hypothesis testing. Relationships of dependence and interdependence. Sources for official statistics. The era of big data.

### Teaching methods

The course is conducted through online distance learning. Attendance is not mandatory, but recommended. The lessons will be recorded and made available to students on the ONELab platform of the Department of Communication and Economics. The teaching is conducted in Italian.

### Assessment methods

The exam will consist of a written test divided into multiple parts: true/false or multiple-choice questions (10-15), open-ended questions (1-5), exercises (1-5). The score assigned to each question/exercise depends on its difficulty. During the written test, it will not be possible to consult textbooks and notes, but it will be allowed to refer to forms and tables provided by the teacher during the lessons. To pass the written test, the student must achieve a passing grade (18/30). The written test will cover the entire course curriculum.

### Learning outcomes

The student will be able to comprehend the basic statistical methodology for collecting, organizing, synthesizing, and quantitatively analysing data related to collective phenomena.
The student will be capable of employing statistical tools to draw conclusions from data, formulate and solve simple problems in probability and statistical inference.
The educational objective is to acquire basic statistical knowledge, enabling the student to choose the appropriate model/indicators to describe a phenomenon, as well as to use statistical analyses independently.
The student will be able to present the results of a data analysis and the underlying methodology clearly and concisely, using appropriate technical language and formalism.
The student will develop a high capacity for independent learning, both by delving into various methodologies in detail and by applying each methodology to different sets of data.
ethodology to different sets of data.

Obbligatori
Slide delle lezioni a cura della docente.
Borra, S., Di Ciaccio, A., Statistica: metodologie per le scienze economiche e sociali, McGraw-Hill, 2015

Altri testi e approfondimenti (non obbligatori)
Iezzi, D.F., Statistica per le Scienze Sociali. Dalla progettazione dell'indagine all'analisi dei dati, Carocci Editore, Roma, 2009
Spiegelhalter, D., L’arte della statistica. Cosa ci insegnano i dati, Einaudi, Torino, 2020 (traduzione italiana)
https://www.istat.it/it/files/2010/09/lineeguida.pdf

Altre brevi letture potranno essere consigliate di volta in volta.

English language only for:
David Spiegelhalter. The Art of Statistics: Learning from Data. London, UK: Pelican, 2019 (versione originale)