Data Analysis
Code
100003
Academic unit
NOVA Information Management School
Credits
6.0
Teacher in charge
Frederico Miguel Campos Cruz Ribeiro de Jesus
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Objectives
•Knowledge and understanding of main techniques for Multivariate Data Analysis.
•Presentation of numerous applications where univariate, bivariate and multivariate analysis associated to data with quantitative variables or qualitative variables, or both, are developed.
•Use of MS Excel and SAS for statistical multivariate real data treatment.
Prerequisites
Statistics and linear algrebra (recomended)
Subject matter
1. Introduction to Multivariate Statistics Data Analysis
2. Principal Components Analysis
3. Factor Analysis
4. Correspondence Analysis
5. Cluster Analysis
6. Multidimensional scaling
Bibliography
•Sharma, S. (1996). Applied Multivariate Techniques. New York, John Wiley & Sons, Inc.
•Reis, E. (2001). Estatística Multivariada Aplicada, Edições Silabo.
•Hair, J. F. (2010). Multivariate Data Analysis, Prentice Hall.
•Branco, João, (2004) – Uma Introdução à análise de clusters, Ed. Sociedade Portuguesa de Estatística
•Course´s slides.
Teaching method
The course is based on theoretical and practical classes.
The classes are aimed at solving problems and exercises.
Evaluation method
Option 1: 1st Test (20%) + 2nd Test (40%) + Group Project (40%)
Option 2: 2nd term Exam (60%) + Group Project (40%)