75422 - Data Mining for Corporate Decisions

Learning outcomes

At the end of the course the student knows the statistical models that are the basis for the extraction of knowledge from large amounts of data. In particular, the student is able to: - structuring a data mining process - choose among the methodological tools, the most appropriate to achieve the objective in question - critically interpret the results.

Course contents

   1.    Introduction to Data Mining: Statistical data: tables, charts, indexes and statistical indicators, quantitative and qualitative data, measurement scales

   2.     Analysis and organization of data: control, integration and data cleaning. Exploratory analysis of univariate and bivariate data

   3.    Analysis of simple and multiple linear regression, terms of extensibility of the model and applications to business problems. Notes on the logistic    regression
   4.    Time series analysis: analysis of short-term, medium-to long-term analysis, the additive model, multiplicative model, ARMA models, ARIMA models (outline)
   5.    Principal Component Analysis ('PCA'): use of the PCA for the synthesis of Customer Satisfaction
   6.    Multiple Correspondence Analysis ('MCA') and Cluster Analysis: uses for market and consumer segmentation

Readings/Bibliography

 

In addition to the slides or handouts provided by the teacher (in http://campus.cib.unibo.it/   ) are recommended:

Biggeri L., Bini M., Coli A., Grassini L., Maltagliati M. (2012) - Statistica per le decisioni aziendali. - Pearson, Milano

Giudici P. (2005) - Data mining : metodi informatici, statistici e applicazioni. - McGraw-Hill,  Milano

Zani S., Cerioli A. (2007) - Analisi dei dati e data mining per le decisioni aziendali. - Giuffrè editore, Milano

Teaching methods

The course is structured in lectures in the classroom, which alternate exercise activities: lectures are detailed in the methodological aspects of the statistical tools presented; in practice, the methods presented in class are applied to data sets relating to specific case studies. The goal of the analysis of the case studies is to consolidate the knowledge acquired during the lectures, and to develop critical skills in the choice of methodological tools most appropriate to the problem under consideration and interpretation of results.

Assessment methods

Submission of a written essay (written in groups or individually), and exposure of the same within the oral test (on all topics of the course).

or alternatively:

Written test (on all topics of the course) with any oral test.

During the written test is not possible to refer to notes, texts, or media.

Teaching tools

Pc; projector; classroom computer lab.

The course material presented by the teacher in class and during exercises is made available by the teacher to link http://campus.unibo.it/  .

Office hours

See the website of Massimiliano Giacalone