'Penerbit Universiti Kebangsaan Malaysia (UKM Press)'
Abstract
Goodness of fit (GOF) test is a statistical technique that can be used to determine whether or
not a data set follows certain statistical distributions. There are various GOF statistics that
can be applied such as Kolmogorov Smirnov (KS), Anderson-Darling (AD) and Cramer- von-
Mises (CV). In this paper a study is conducted to investigate the performance of several
selected goodness of fit tests which include KS, AD, CV, three test statistics of Zhang and a
proposed modified GOF test which incorporates a variance stabilising transformation. The
performance of these tests is studied for testing normal and logistic distributions for various
sample sizes. It is found that Zhang’s test is the most powerful and followed closely by our
proposed GOF tes