CLUSTER ANALYSIS AND PRINCIPAL COMPONENTS ANALYSIS IN THE EVALUATION OF MULTIVARIATE TABLES (N X P).

Paula Roberto CURI[1]

Alexandre ALVES2

Patrick Johannes BECKERS[2]

Lúcia TERADA[3]

§    ABSTRACT: The situation of the countries is studied based on a collection of basic, health, economic and cultural indicators published by UNICEF in 1990. It was used multivariate statistical methods: Principal Components Analysis and Cluster Analysis. The study was performed to countries of all the continents, with 36 countries whose choice criterion was to include countries with complete information (to the 16 used variables) and of the most varied degrees of development. The first principal component was interpreted as a measure of the "development degree "which made it possible the order of the countries. The most discriminating variables were the childish death rates and death of children with less than 5 years old and the expectation of living.

§    KEYWORDS: Principal components analysis; Cluster analysis; multivariate tables.

 



1Serv. De Estatística e Computação – Faculdade de Medicina, Veterinária e Zootecnia – UNESP – 18610-000.

[2] Acadêmicos de Zootecnia – FMVZ – UNESP – 18618-000 – Botucatu – SP. Bolsistas da FAPESP.

[3] Acadêmicos de Zootecnia – FMVZ – UNESP – 18618-000 – Botucatu – SP. Bolsistas da CNPq.