How to move beyond classical null hypothesis testing: A black bear story
This short paper illustrates that testing the traditional null hypothesis is not always the appropriate strategy. Half in jest we use a story about a black bear to illustrate that there are some discrepancies between the formal use of the p¬-value and the way it is often used in practice. I argue that more can be learned from data by evaluating informative hypotheses, than by testing the traditional null hypothesis. It will be shown that Bayesian model selection can be used to evaluate informative hypotheses using a real longitudinal study by way of example. Finally I will conclude that all criticisms of classical null hypothesis testing aside, the best argument for evaluating informative hypotheses is probably that many researchers want to evaluate their expectations directly, but have been unable to do so because the statistical tools were not yet available. As this paper illustrates, these tools are ready to be used for any researcher within the social sciences.
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