The probability value (p-value) of a statistical hypothesis test is the probability of getting a value of the test statistic as extreme as or more extreme than that observed by chance alone, if the null hypothesis Ho, is true.
It is the probability of wrongly rejecting the null hypothesis if it is in fact true.
It is equal to the significance level of the test for which we would only just reject the null hypothesis. The p-value is compared with the desired significance level of our test and, if it is smaller, the result is significant. That is, if the null hypothesis were to be rejected at the 5% significance level, this would be reported as "p < 0.05".
Small p-values suggest that the null hypothesis is unlikely to be true. The smaller it is, the more convincing the evidence is that null hypothesis is false. It indicates the strength of evidence for say, rejecting the null hypothesis H0, rather than simply concluding "Reject Ho" or "Do not reject Ho".
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© 2008 Six Sigma Terminology - This dictionary provides useful terms and definitions for Six Sigma understanding.
This dictionary provides useful terms and definitions for Six Sigma understanding.
