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37154 - Statistical Models for the Assessment

Academic Year 2020/2021

                
                        Docente:
                        Alessandro Lubisco
                    
                        Credits:
                        8
                    
                        SSD:
                        SECS-S/01
                    
                        Language:
                        Italian
                    
                        Moduli:
                        
                            Alessandro Lubisco
                            (Modulo 1)
                        
                            Alessandro Lubisco
                            (Modulo 2)
                        
                            Valentina Sansivieri
                            (Modulo 3)
                        
                        Teaching Mode:
                        
                                    Traditional lectures (Modulo 1)
                                
                                    Traditional lectures (Modulo 2)
                                
                                    Traditional lectures (Modulo 3)
                                
                            Campus:
                            Rimini
                        
                            Corso:
                            First cycle degree programme (L) in
                            Finance, Insurance and Business (cod. 8872)

                                Also valid for
                                
                                    First cycle degree programme (L) in
                                    
                                        Business Economics (cod. 8848)
                                    
                            Teaching resources on Virtuale

Learning outcomes

At the end of the course the student is able to analyze multivariate data with advanced statistical methods and using statistical software.

Course contents

Part I

The steps of a statistical survey.
Review of multiple linear regression
Basics of test development and validation.
Latent variable models for categorical data (item response theory models)

Parts II and III

Recall of principal component analysis
Factor analysis
Structural equation models (LISREL approach)

Computer lab activies on the analysis of case studies using specific software (Excel, R, SPSS).

Readings/Bibliography

Compulsory reading

Teacher's lecture notes available on the platform "Insegnamenti online - Supporto online alla didattica" https://iol.unibo.it/

Suggested textbooks

S. Mignani, A. Montanari (1997). Appunti di analisi statistica multivariata, Esculapio, Bologna, Second edition (chapters 1-2 linear regression model, chapter 3 principal component analysis, chapter 4 factor analysis)
S. Borra, A. Di Ciaccio (2014). Statistica – metodologie per le scienze economiche e sociali, terza edizione, McGraw-Hill, Milano (chapters 16-17 linear regression model).
D. J. Bartholomew et al. (2002). The analysis and interpretation of multivariate data for social scientists, Chapman & Hall (chapters 5-6-7 principal component analysis, factor analysis).

Teaching methods

Frontal and/or on line lessons according to sanitary provisions.

Assessment methods

Oral exam to assess the knowledge of the statistical methods both from a methodological and from a practical point of view. The oral exam deals with both the statistical theory and the interpretation of outputs produced with the software Excel, R and SPSS.

It is possible to give an intermediate oral exam on the contents of module I in the November week devoted to intermediate exams. If the grade is sufficient (at least 18/30), it will be possible to complete the exam on the contents of modules II and III within the next September session. The final grade is given by the arithmetic mean of the grade in the module I and the grande in the modules II and III. If the grade is not sufficient, it will be necessary to give the total oral exam.

Teaching tools

Slides and lab material available on line.

Office hours

See the website of Alessandro Lubisco

See the website of Valentina Sansivieri