Análise de Dados Multivariados

Objectivos

The objective of data analysis is to extract the relevant information contained in the data which can then be used to solve a given problem.

Caracterização geral

Código

400013

Créditos

6.0

Professor responsável

Jorge Morais Mendes

Horas

Semanais - A disponibilizar brevemente

Totais - A disponibilizar brevemente

Idioma de ensino

Português. No caso de existirem alunos de Erasmus, as aulas serão leccionadas em Inglês

Pré-requisitos

Statistics and linear algebra (recommended)

Bibliografia

  • Everitt, B. and Hothorn, T. (2011). An Introduction to Applied Multivariate Analysis with R, Springer
  • Johnson, R.A and Winchern (2007), D. W., Applied Multivariate Statistical Analysis, 6th edition, Pearson Prentice Hall
  • Sharma, S., (1996) Applied Multivariate Techniques, John Wiley & Sons
  • Timm, N. H., (2002) Applied Multivariate Analysis, Springer
  • Jr., W. C. Black, B. J., Hair, J. F. (2013). Multivariate Data Analysis-Pearson, 7th edition, Education Limited.

Método de ensino

The course is based on theoretical-practical and practical classes. Practical classes and problem-solving
oriented.

Método de avaliação

  • (50%) Final exam (1st and 2nd rounds)
  • (50%) Project (optional)
  • Final grade: maximum (Final exam grade;0.5*(Final exam grade)+0.5*Project grade))

A minimum grade of 8.5 is required in the final exam to pass.

Conteúdo

  1. Multivariate data analysis basics
  2. Getting started with R. First R tutorial
  3. The multivariate normal distribution
  4. Graphical display of multivariate data
  5. Principal components analysis
  6. Factor analysis
  7. Cluster analysis
  8. Correspondence analysis and multidimensional scaling