Insegnamento a.a. 2013-2014

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, finance, 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. The course gives support for the use of the software program SPSS, a widely used software package in the social sciences, though students are free to use other softwares.

Course Content Summary

• Introduction to applied research, research design, research question, causality
• Sampling and data sources, finding data for research projects
• Regression analysis: The simple one regressor case, multivariate regression, assumptions and properties, violation of assumptions and remedies, time series analysis and seasonality.
• One and two factors ANOVA
• Factor analysis: model, extraction, rotation, interpretation
• Scale construction and evaluation: reliability analysis and composite scores
• Cluster Analysis
• Regression analysis revisited: regression analysis in combination with factor analysis and cluster analysis, binary response models

Detailed Description of Assessment Methods

The written exam makes up 70% of the grade and the project 30%.

The exam is written and lasts two hours. It is possible to take the written exam in two partial parts. In this case, the first partial must be passed (18/30) to became eligible to do the second partial.
The exam and the project are valid until the end of AY 2013-14.

Textbooks

• P. Newbold, W.L. Carlson, B. Thorne, Statistics for Business and Economics and Student CD, 6/E, Prentice Hall (International Edition), 2007. For regression and ANOVA.
• Lecture notes (sampling, data sources, research design, factor analysis, scale reliability and cluster analysis)

Prerequisites