93296 - Statistical Methods for Business Applications

Academic Year 2023/2024

  • Moduli: Sergio Brasini (Modulo 1) Federica Galli (Modulo 2)
  • Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
  • Campus: Rimini
  • Corso: First cycle degree programme (L) in Business Economics (cod. 8848)

Learning outcomes

The course aims to provide the necessary knowledge for the collection and analysis of data of interest for the management of the firm. The course introduces students to the main statistical methodologies in order to:

- analyze business data for supporting managerial decisions;

- describe sampling techniques to collect data of business interest;

- make use of regression models to investigate the causes of business phenomena and generate forecasts;

- construct indicators for measuring productivity of firms.

The increasing availability of data in the information society has highlighted the need for appropriate methodologies and tools for quantitative decision-making processes. With this in mind, the presentation of statistical methods is always followed by examples and illustration of business cases.

Course contents

First Module

1. The use of Statistics for business management:

- Availability and production of statistical information

- Internal sources

- External sources

2. The production of ad hoc data through sample surveys:

- Probabilistic samples and reasoning samples

- Sample selection 

- Types of lists and methods of data collection

- Presentation of the main sampling methods

- Sample size determination

- Design of the questionnaire

- Non-sampling errors and data quality control

- Evaluation of the costs of survey

Second Module

3. Index numbers and productivity measurement:

- Statistical quotients 

- Simple and synthetic index numbers 

- Definitions of productivity and efficiency 

- Production functions 

- Productivity measures (Hicks-Moorsten total factor productivity index; Malmquist productivity index)  

 4. Regression models for business management:

- References to correlation measures 

- Simple and multiple linear regression 

- Gauss-Markov assumptions and residual analysis


Lecture notes available on http://virtuale.unibo.it/

L. Biggeri, M. Bini, A. Coli, L. Grassini e M. Maltagliati, Statistica per le decisioni aziendali, Pearson, Milano, second edition, 2023.



Teaching methods


It is essential that students log in to Virtuale platform by logging in (button at the top right) with their University credentials, then going to "All courses" they look for the teaching of "Metodi statistici per le applicazioni aziendali" and register. Here the slides and other materials used in class will be made available. In addition, in case of need, teachers can send communications to the mailing list of subscribers relating to the course and how to take the exam.

The lessons will be interactive, so students are invited to actively participate with observations, questions and reports. Exercises and case studies will also be proposed, in order to provide practical demonstrations on the use of the theoretical concepts addressed.

Assessment methods

The exam is aimed at evaluating the skills and the critical abilities developed by the students.

The course is divided into two teaching modules. For the former, the verification takes place through an oral examination lasting about 20 minutes. For the second, the assessment of learning takes place through a written examination lasting about 90 minutes. During each examination the students answer to 4-5 questions. It's possible to agree to carry out an optional partial test before the start of the lessons of the second teaching module. 

Registration for the exam is compulsory, and students have to register through AlmaEsami platform according to the general rules of the University of Bologna. It's not possible to register before the opening date or after the closing date of the scheduled time window. Students who are unable to enroll are required to promptly contact the teaching support staff to report the problem.

The mark is out of 30 points. It derives from the arithmetic mean of the ratings of both teaching modules. The minimum required to pass each module and the whole exam is 18/30.

Teaching tools

Video-projector and pc.

On Virtuale platform teaching materials and slides used during the lessons will be made available.

Office hours

See the website of Sergio Brasini

See the website of Federica Galli


Industry, innovation and infrastructure

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.