Testing the Bayesian confidence hypothesis

Bayesian Fuzzy Hypothesis Testing with Imprecise Prior Distribution

This paper considers the testing of fuzzy hypotheses on the basis of a Bayesian approach. For this, using a notion of prior distribution with interval or fuzzy-valued parameters, we extend a concept of posterior probability of a fuzzy hypothesis. Some of its properties are also put into investigation. The feasibility and effectiveness of the proposed methods are also cla...

Confidence Intervals and Hypothesis Testing.∗

If you have just two discrete hypotheses, then a hypothesis test is simply an application of Bayes’ Theorem. You check to see whether your data can reasonably be explained by that boring old null hypothesis (conventionally called H0), or not. To test H0, you need to compare it to one other model. One never tests a hypothesis in isolation; it is tested against an alternative (typically called H1...

Bayesian Hypothesis Testing 1 Running head: BAYESIAN HYPOTHESIS TESTING The Need for Bayesian Hypothesis Testing in Psychological Science

Visual Hypothesis Testing with Confidence Intervals

A simple visual method of comparing means given normal %~. confidence intervals is proposed. Monte Carlo simulations were used to derive a visual rule of thumb that can be used to test the null hypothesis of equal means, given the confidence intervals of the means, and the sample sizes (or degrees of freedom). The type-1 error rate of the test is approximately .05. The rule involves accepting t...

Bayesian hypothesis testing for proportions

Most clinical trials contain tests on proportions, usually they are answered by means of the Frequentist approach, nevertheless another valid option could be to solve them using a Bayesian approach. The Bayesian approach has the advantage that it is not restricted to only one alternative hypothesis. Moreover, the hypotheses to be tested do not necessarily overlap. In this paper we show a SAS® m...