93296 - Statistical Methods for Business Applications

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. Regression models for business management and forecasting:

- References to the analysis and measurement of multiple linear correlation

- Multiple linear regression and Gauss-Markov assumptions

- Forecasting and evaluation of predictive ability in general

- Analysis of time series: visual inspection, stationarity and non-stationarity, autocorrelation and correlogram

- Decomposition of time series and estimation of components with moving averages, seasonality coefficients and various analytical functions for deterministic trends

- Forecasts based on models estimated with ordinary least squares, simple exponential smoothing and Holt-Winters methods

4. Indicators for measuring productivity of firms:

- Definition of productivity

- Hicks-Moorsten total factor productivity index

- Malmquist productivity index

Readings/Bibliography

L. Biggeri, M. Bini, A. Coli, L. Grassini e M. Maltagliati, Statistica per le decisioni aziendali, Pearson, Milano, second edition, 2017.

Teaching methods

Lessons.

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. The verification of both modules takes place through an oral examination of the duration of nearly 20 minutes. During each examination the students answer to 3-4 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 Annalisa Stacchini