Learning outcomes

The course aims at providing students with the statistical methods for the analysis of business data from different areas of a firm, supporting the decision making process within a firm. Topics are introduced by illustrating common business issues whose solutions can be found by applying statistical methods. By the end of the course, students will be able to:
- select the proper statistical method for a specific business analysis;
- perform preliminary analysis of business data, and organize data in a data structure useful for the following statistical analysis;
- apply univariate and multivariate statistical methods to business data;
- interpret results and provide managers with synthetic information for business decisions.

Program

Data sources and statistical information for business.
Statistical indicators for business:
- simple index numbers;
- composite index numbers;
- consumer price indices and producer price indices;
- industrial production index.
Descriptive statistics for analysing business data:
- statistical indicators with application to customer data;
- the Lorenz curve and the analysis of customer concentration;
- statistical methods for customer segmentation: RFM and ABC analysis.
Multivariate statistical analysis of customer and business data:
- cluster analysis;
- principal component analysis.
Introduction to statistical quality control:
- control charts for qualitative data;
- control charts for quantitative data.
Business forecasting:
- delphi analysis;
- smoothing techniques: moving averages and exponential smoothing;
- techniques for decomposing economic time series.


Suggested book: B. Bracalente, M. Cossignani, A. Mulas (2009) Statistica Aziendale, McGraw-Hill, Milano.

Examination Methods

A mandatory written exam and an optional oral exam. Written exam is broken down into two parts:
- The first part comprises short-answer questions about the various topics of the course.
- The second part comprises i) an open question about a specific topic of the course, ii) two exercises in which students are asked to apply statistical methods for business data analysis and to interpret the results.
Oral exam is optional and a cut-off score on the written exam is required to do the oral exam.