Studying at the University of Verona

Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.

Study Plan

This information is intended exclusively for students already enrolled in this course.
If you are a new student interested in enrolling, you can find information about the course of study on the course page:

Laurea magistrale in Management e strategia d’impresa - Enrollment from 2025/2026

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.

1° Year

ModulesCreditsTAFSSD
1 module between the following
9
B
SECS-P/07
1 module between the following
1 module between the following
1 module between the following
English B2 level
4
F
-

2° Year  activated in the A.Y. 2021/2022

ModulesCreditsTAFSSD
1 module between the following
1 module between the following
1 module between the following
Stage
5
F
-
Final exam
15
E
-
ModulesCreditsTAFSSD
1 module between the following
9
B
SECS-P/07
1 module between the following
1 module between the following
1 module between the following
English B2 level
4
F
-
activated in the A.Y. 2021/2022
ModulesCreditsTAFSSD
1 module between the following
1 module between the following
1 module between the following
Stage
5
F
-
Final exam
15
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S008094

Academic staff

Catia Scricciolo

Coordinator

Credits

6

Language

Italian

Scientific Disciplinary Sector (SSD)

SECS-S/03 - ECONOMIC STATISTICS

Period

primo semestre (lauree magistrali) dal Oct 5, 2020 al Dec 23, 2020.

Learning outcomes

The course aims to provide the basic knowledge for the collection, management and analysis of data of interest in the managerial field. Students' previous statistical knowledge will be integrated with the main statistical sampling techniques for data collection, some of the most widespread techniques for the analysis of time series data, the multiple linear regression, and the most recent techniques for data science in the business context. All these techniques will be discussed in specific areas of application: market research, customer analysis, management control, production process control, sales analysis and forecasting. Special attention will be devoted to some of the most widespread software for data science and business intelligence. At the end of the course, students should demonstrate a good level of understanding both theoretically and practically of the main statistical methods for the analysis of business phenomena, in the light of the available data and the managerial needs. They should also be able to interpret critically the gathered information and the results obtained from the analyses with the aim to supply useful suggestions in support of business decisions.

Program

1) Data sources:
Primary and secondary data.
Internal and external data sources.

2) Probabilistic and non-probabilistic sampling for sample survey:
Review of estimation theory.
Probabilistic sampling design.
Probabilistic sampling for variables.
Determination of the sampling size.

3) Customer analysis:
Pareto chart.
Concentration analysis. The Gini coefficient.

4) Statistical Analysis of sales data. Time Series analysis:
Time series decomposition in trend, seasonality and error.
Moving averages method.

5) Introduction to statistical quality control:
Statistical process control.
Control charts for variables.

6) Introduction to Business Intelligence. Techniques of data visualization.



The course is taught by lectures.
Lecture slides and other learning materials are available on the e-learning website.

Reference texts
Author Title Publishing house Year ISBN Notes
M. R. Middleton Analisi statistica con Excel Apogeo, Milano 2004
D. Clark Beginning Power BI: A Practical Guide to Self-Service Data Analytics with Excel 2016 and Power BI Desktop (Edizione 2) Apress 2017 9781484225769
R. Sleeper Practical Tableau: 100 Tips, Tutorials, and Strategies from a Tableau Zen Master O'Reilly Media, Inc. 2018 9781491977316
B. Bracalente, M. Cossignani, A. Mulas Statistica Aziendale McGraw-Hill 2009
Luigi Biggeri, Matilde Bini, Alessandra Coli, Laura Grassini, Mauro Maltagliati Statistica per le decisioni aziendali (Edizione 2) Pearson Italia 2017

Examination Methods

Given the COVID-19 sanitary emergency, more information on examination method will be provided as soon as possible according to the guidelines adopted by the University.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE