This paper presents two Bayesian alternatives to the chi-squared test for determining whether a pair of categorical data sets were generated from the same underlying distribution. It then discusses such alternatives for the Kolmogorov-Smirnov test, which is often used when the data sets consist of real numbers.

In symbolic data analysis, the values of the variables can be, among others, intervals. The algebraic structure of these variables leads us to adapt dissimilarity ones to be able to study them. The Kolmogorov-Smirnov criterion is used as a test selection metric for decision tree induction. For this criterion, the values taken by the explanatory variables have to be ordered. We have been interes...

This study was undertaken to compare several methods of evaluating the common assumption that laboratory data may be treated as if they had been drawn from an underlying Gaussian distribution. As had been described earlier, the usual Kolmogorov-Smirnov test was found to be unsatisfactory due to its sensitivity to rounding. In addition, a recently suggested modification also was shown to be unsu...

many commonly used statistical methods require that the population distribution be nearly normal. unfortunately, in some papers the one-sample kolmogorov-smirnov test has been used for testing normality while the assumptions of applying this test are not satisfied. to conduct this test, it is assumed that the population distribution is fully specified. in practical situation where the mean and ...