ABSTRACT
ABSTRACT: The objective of this study was to apply multivariate techniques, canonical discriminant analysis, and multivariate contrasts, indicating the most favorable inferences in the evaluation of pure lines of beans. The study was conducted at the experimental field of the Institute for Breeding and Molecular Genetics, in Lages, SC, Brazil. The experiment was composed of 24 pure lines of beans from the Santa Catarina test of cultivars. Plant height, numbers of pods and grains per plant, and stem diameter were the variables measured. The complete randomized block design was used with four replications. The data were subjected to multivariate analysis of variance, canonical discriminant analysis, multivariate contrasts and univariate contrasts. The first canonical discriminant function has captured 81% of the total variation in the data. The Scott-Knott test showed two groups of inbred lines at the average -of scores of the first canonical discriminant function. It was considered that testing hypotheses with the canonical scores may result in loss of information obtained from the original data. Multivariate contrasts indicated differences within the group formed by the Scott-Knott test. The canonical discriminant analysis and multivariate contrasts are excellent techniques to be combined in the multivariate assessment, being used to explore and test hypotheses, respectively.
RESUMO: O objetivo deste estudo foi aplicar técnicas multivariadas (análise discriminante canônica e contrastes multivariados) indicando as inferências mais vantajosas na avaliação de linhas puras de feijão. O estudo foi conduzido na área experimental do Instituto de Melhoramento e Genética Molecular em Lages, SC. O experimento foi composto por 24 linhas puras de feijão provenientes do ensaio catarinense de cultivares. Os caracteres mensurados foram: estatura da planta, números de legumes e grãos por planta e diâmetro do caule. Foi usado o delineamento experimental em blocos casualizados, com quatro repetições. Os dados foram submetidos à análise de variância multivariada, análise discriminante canônica, contrastes multivariados e univariados. A primeira função linear discriminante canônica captou 81% da variação total contida nos dados. O teste de Scott-Knott formou dois grupos de linhas puras na média dos escores da primeira função linear discriminante canônica. Considera-se que testar as hipóteses com os escores canônicos pode causar perda de informações valiosas obtidas pelos dados originais. Os contrastes multivariados evidenciaram diferenças dentro do grupo formado pelo teste de Scott-Knott. A análise discriminante canônica e os contrastes multivariados são técnicas excelentes para serem combinadas na avaliação multivariada, sendo efetuadas para explorar e testar hipóteses, respectivamente.
ABSTRACT
Objective To investigate the statistical.method for analyzing nurse job burnout Data. Methods Hotelling T2 test and multivariate analysis of variance(MANOVA)were used to analyze nurse job burnout datum. Results There was statistical significance between different cities,different ethnieities in the personal achievements,hut from three dimensions of the whole job burnout,there are no statistical sig-nificant differences among different cities, different ethnicities and different ages. Conclusions The use of Hotelling T2 test and multivariate analysis of variance to analyzing nurse job burnout data, not only ob-tain overall conclusion, and further use of single-variable analysis may also gain comparative results of each dimensions.