Abstract
A distinction is made between statistics based on scientific theory and theory-free statistics. Both are valuable and should be included in most research reports. Conventional simple hypothesis testing is often ambiguous; it could be in either class depending on the experimental hypothesis. A priori planned contrasts and Bayesian inference with specific priors are examples of theory-based statistics, with the former having many of the virtues of the latter. A new simple computational method devised by Pruzek is illustrated for determining the weights of an a priori contrast using “guessed” means. Such statistics are desirable to maximize power in tests of the experimenter’s predictions. Theory-free statistics are desirable to permit others to test alternative interpretations of the data.
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