It is the probability of correctly rejecting the null hypothesis when it isįalse and thereby detecting a real difference when it does exist. Generally acceptable value of α is ≤0.05 and that of β is ≤0.2 Type I and Type II Error: Rejecting null hypothesis when it is true is called Type I error (α), and accepting null hypothesis when it is false is called Type II error (β). The benefit of using p-value is that it calculates a probability estimate, we can test at any desired level of significance by comparing this probability directly with the significance level.
P-value, on the other hand, is defined as the probability to the right of the respective statistic (Z, T or chi). P value: P denotes the probability of obtaining a result equal to or “more extreme” than what is actually observed, assuming that the null hypothesis is true.
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