Comparação da robustez de alternativas do teste de igualdade de duas médias populacionais sob não normalidade por simulação Monte Carlo

Abstract

This work aimed to evaluate the risks of committing type I and type II errors in non normal populations by means of computational simulation and to compare three tests usually applied. It was compared the t test with the approach of the degrees of freedom proposed by Satterthwaite (1946), t with the degrees of freedom given by v = min ( n 1 - 1, n 2 - 1) and bootstrap method under different distributions of probability. Under non normal distribution the t with Satterthwaite adjustment of degrees of freedom and with v = min ( n 1 - 1, n 2 - 1) degrees of freedom did not control type I error probabilities. The bootstrap criterion controlled the type I error rates and presented equivalent power being considered robust with the violation of the normality assumption. The t test under non normal distribution with Satterthwaite adjustment of degrees of freedom with samples of different sizes presented type I error rates greater than the nominal levels.