1. Início
  2. NOVA Information Management School
  3. Pós-Graduação em Sistemas Estatísticos
  4. Pós-Graduação em Sistemas Estatísticos com Especialização em Estatísticas Oficiais
  5. Análise de Dados Multivariados

Análise de Dados Multivariados

Objetivos

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: máximum (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