INFORMATION MEASURES - STATISTICAL CONFIDENCE-LIMITS AND INFERENCE

This paper presents tested statistical methods for reducing sampling bias in, for assigning approximate confidence bounds to, and for testing hypotheses about information-theoretic measures used in the study of animal communication and in behavioral sequence analysis. These procedures are also applicable in fields other than animal behavior, including psychology and ecology. Results of a Monte Carlo evaluation of the methods, including comparison of these techniques with possible alternative procedures, are presented. © 1978.