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.
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:
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.
|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|
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.