Application of principal component analysis as a technique to obtain synthetic indices of environmental quality

Abstract

The purpose of this study was to validate the application of the multivariate statistical analysis, specifically, the principal components analysis, to transform a set of simple indicators of environmental quality to a new set of incorrelacionados composite indicators or components. Applied design research was quantitative, not experimental, cross-sectional, correlation and data collection technique was the documentary analysis, using environmental statistics 2010 Yearbook published by the INEI as a source of information on ten environmental indicators. Processing and analysis of data, using the SPSS software, allowed to obtain the matrix of correlations, the principal components and the matrix of coefficients for the calculation of the scores in the components. Three main components were obtained, the first grouped five indicators relating to quality of life in the home, the second grouped two indicators referring to the environmental temperature and the third grouped three indicators of environmental quality out of the housing. The value and type of correlation between indicators for each component is consistent with the nature or class of these. Finally, using the program Excel was calculated a partially synthetic index for the Department of La Libertad.