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Abstract
A data-screening procedure for identifying the dynamic structure of psychological data series is presented, based on information theory measures. It can generate signatures of random, periodic, and edge-of-chaos series which then serve as a preliminary step to pursuing fuller analyses, using appropriate statistics that are already available in software. It is no longer necessary to assume that real data are either linear, noisy, or periodic in order to obtain measures of the matching of theory to data. A glossary of technical terms is appended.