A p-value can be simply defined as the probability that under a specified statistical model a statistical summary of the data (e.g., the mean difference between two groups) would be equal to or more extreme than its observed value. p-values do not measure the probability that the studied hypothesis was true, or the probability that the data were produced by random chance alone (Wasserstein & Lazar, 2016). What researchers usually want is p(HjD), the probability that a research hypothesis was true, given the data. Three examples were shown that analyzed using the probability that a hypothesis was true, instead of p-values. A peer-reviewed policy using a new standard for publishing useful papers for society was proposed.