The Strength of Statistical Evidente

An important role of statistical analysis in science is for interpreting and communicating statistical evidente per se showing “what the data say.” Although standard methods (hypothesis testing, estimation, confidence intervals) are routinely used for this purpose, the theory behind those methods contains no defined concept of evidente, and no answer to the basic question, “When is it correct to say that a given body of data represents evidente supporting one statistical hypothesis over another?” Because of this theoretical inadequacy, these applications are guided largely by convention, and are marked by unresolvable controversies (such as those over the proper use and interpretation of “p-values” and adjustments for multiple testing or optional stopping). The Law of Likelihood represents the missing concept, and its adoption in statistical theory leads to a frequentist methodology that avoids the logital inconsistencies pervading current methods, while maintaining the essential properties that have made those methods into important scientific tools.