Sampling distributions of the entropy in visual scanning

Abstract

Identifying true statistical dependencies in visual-scanning data involves showing that the observed scanning pattern is significantly more ordered than that which would be produced by a stratified random-sampling model. In the past, entropy has been used as the index to measure statistical order or dependency. Due to the unknown nature of the underlying sampling distributions of entropy, however, researchers have had to use relatively less powerful nonparametric statistical tests to determine significance. In this paper we present relevant portions of the family of sampling distributions of entropy and show that they are sufficiently normally distributed to allow the use of a more powerful parametric statistical test when attempting to distinguish among the different models of sampling. © 1989 Psychonomic Society, Inc.