37993 - Business Statistic

Course Unit Page

Academic Year 2018/2019

Course contents

The course covers statistical techniques useful for the collection, organization and analysis of business data. The results of these analyzes can be helpful for managerial decisions, often made under conditions of uncertainty. The course is application-oriented, with the use of SAS statistical software, of the mentioned methods to business data, in the context of specific issues/scenarios of the business management.

1. Statistics and the firm.

2. Business data base. Sample surveys. Sampling error. Random and non-random samples. Panel and rotating panel surveys. Choice of the sample dimension. How to calculate and correct sampling weights. Non sampling error.

Some official sources of data. The Istat and AcNielse consumer and expenditure survey. The Bank of Italy survey on income.

The data matrix.

3. Methods for forecasting industry demand and sales. Exogenous and endogenous methods for forecasting.

Multiple regression model. Basic assumptions. Parameters estimation and interpretation. OLS Estimators properties. Hypothesis testing for the model and for parameters. Residuals analysis. Comparison between nested models. The multicollinearity problem. The inclusion of qualitative explanatory variables in the model. Punctual and interval forecasting. Selection of explanatory variables.

Non linear regression models.

Examples .

4. The market segmentation. The distance-matrix.

"A priori" and "A posteriori" classification methods.

"A posteriori" methods: hierachical cluster analysis. Phases, methods, choice of the number of groups and description of groups.

"A posteriori" methods: non-hierachical cluster analysis. Phases, k-means method, choice of the number of groups and description of groups.


In the last part of the course students who attend the course are request to carry out a sample survey on a topic agreed. This implies the choice of the sampling strategy, the drafting of the questionnaire, the interviews, editing of data and analysis of data by using the statistical techniques studied during the course.


Slides (for students attending the course).

Brasini, Freo, Tassinari e Tassinari, Statistica aziendale e analisi di mercato, Il Mulino: Bologna, 2002, Capitoli: I (da 1.1 a 1.6); V (da 5.1 a 5.2); VI (da 6.1 a 6.2), VII (par. 1, 2, 3, 4, 6).

“Il campionamento statistico”, G. Cicchitelli, G. Montanari, A. Herzel, 1997, Il Mulino (parti relative alla costruzione dei pesi per vari disegni di campionamento).

Cap. 13 “La regressione lineare multipla”, scaricabile sul sito www.apogeonline.com/2006/libri/88-503-2357-3/ebook/2357-cap13.pdf, in Levine D.M., Krehbiel T., Berenson M.L., Statistica II ed., Apogeo: Milano.

“Introduzione all'econometria”, J.H. Stock e M.W. Watson (edizione italiana a cura di F. Peracchi), seconda edizione, 2009, Pearson Education, cap. 8.

Zani, Analisi dei dati statistici – Osservazioni multidimensionali, Giuffré: Milano, 2000. Capitolo 5.

Teaching methods

Lectures and laboratory exercises.

Assessment methods

First partial exam: oral exam on the topics covered in the first part of the course.
Second partial exam: written and oral report on a practical work consisting in the application in SAS of methods studied in the second part of the course on data collected in the sample survey carried out by the class. The practical work may be carried out individually or in group of two people. If it is carried out in group, members of the group present a unique report ad share the oral presentation of the work, highlighting the contribution provided by both members of the group.
The final vote is the average of votes taken in the two partial exams.
Students who do not take the first oral exam, take both exams (oral test and presentation of the practical work) at the end of the course.

Office hours

See the website of Silvia Pacei