Master’s degree in Management and business strategy

Statistics for Business

Course code
4S008094
Name of lecturers
Veronica Cicogna, Catia Scricciolo
Coordinator
Veronica Cicogna
Number of ECTS credits allocated
6
Academic sector
SECS-S/03 - ECONOMIC STATISTICS
Language of instruction
Italian
Site
VICENZA
Period
primo semestre (lauree magistrali) dal Oct 5, 2020 al Dec 23, 2020.

Lesson timetable

Go to lesson schedule

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.

Syllabus

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 books
Author Title Publisher Year ISBN Note
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

Assessment methods and criteria

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.



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