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In many fields of research null hypothesis significance tests and p valuesare the accepted way of assessing the degree of certainty with which researchresults can be extrapolated beyond the sample studied. However, there are veryserious concerns about the suitability of p values for this purpose. Analternative approach is to cite confidence intervals for a statistic ofinterest, but this does not directly tell readers how certain a hypothesis is.Here, I suggest how the framework used for confidence intervals could easily beextended to derive confidence levels, or "tentative probabilities", forhypotheses. I also outline four quick methods for estimating these. This allowsresearchers to state their confidence in a hypothesis as a direct probability,instead of circuitously by p values referring to an unstated, hypothetical nullhypothesis. The inevitable difficulties of statistical inference mean thatthese probabilities can only be tentative, but probabilities are the naturalway to express uncertainties, so, arguably, researchers using statisticalmethods have an obligation to estimate how probable their hypotheses are by thebest available method. Otherwise misinterpretations will fill the void. Keywords: Confidence, Null hypothesis significance test, p value, Statisticalinference

Simple Methods for Estimating Confidence Levels, or Tentative Probabilities, for Hypotheses Instead of P Values