Course 2007-2008 a.y.

5305 - APPLIED RESEARCH


CLEA - CLAPI - CLEFIN - CLELI - CLEACC - DES - CLEMIT - DIEM - CLSG

Department of Decision Sciences

Course taught in English

Go to class group/s: 31
CLEA (6 credits - I sem. - AI) - CLAPI (6 credits - I sem. - AI) - CLEFIN (6 credits - I sem. - AI) - CLELI (6 credits - I sem. - AI) - CLEACC (6 credits - I sem. - AI) - DES (6 credits - I sem. - AI) - CLEMIT (6 credits - I sem. - AI) - DIEM (6 credits - I sem. - RR) - CLSG (6 credits - I sem. - AI)
Course Director:
FRANCESCO CANDELORO BILLARI

Classes: 31 (I sem.)
Instructors:
Class 31: BARBARA CHIZZOLINI


Course Objectives

The purpose of the course is to enable students to structure and conduct autonomously a research project based on the analysis of data sets concerning business, economics and in general the social sciences. The course presents a set of tools with an applied perspective, providing the methodological knowledge that is necessary to conduct such projects with a fair level of competence and with the ability to choose appropriate statistical methods for various problems. Lectures providing motivation, methods and examples alternate with applied workshops (to be held in the computer lab) in which students participate actively. The lectures supply the students with the basic concepts and techniques of multivariate data analysis, which is then linked to applications and data sets relevant for the students. Lectures and tutorials are also scheduled in order to introduce the students to the use of the widely-used package SPSS for the analysis of multivariate data.

 


Course Content Summary

  • Introduction to applied research using multivariate techniques.
  • Sources of data. Finding data for a research project.
  • Factor Analysis.
  • Cluster Analysis.
  • Regression Analysis: the simple one-regressor case.
  • Regression Analysis: the multivariate case.
  • One and Two factors ANOVA.
  • Generalized Linear Models: Logistic Regression.
  • Poisson models.
  • Longitudinal categorical data.

Detailed Description of Assessment Methods

Gli studenti dovranno svolgere settimanalmente degli assignments e sostenere un esame scritto. I primi incideranno per il 60% sul voto finale; l'esame per il 40%.

Software: web browser, piattaforma online di apprendimento Bocconi, SPSS, Excel.


Textbooks

Gli appunti del corso saranno reperibili insieme ad alcuni indirizzi web utili (ad es. http://www2.chass.ncsu.edu/garson/pa765/statnote.htm) e ai riferimenti agli articoli e testi d'esame.

Exam textbooks & Online Articles (check availability at the Library)
Last change 12/06/2007 11:54