Significant value of "p" is: March 2010

Ans. D: 0.05 In statistical hypothesis testing, the p-value is the probability of obtaining a test statistic at least as extreme as the one that was actually observed, assuming that the null hypothesis is true. The lower the p-value, the less likely the result is if the null hypothesis is true, and consequently the more "significant" the result is, in the sense of statistical significance. It has become customary to regard as significant when p is less than 0.05 (1 in 20) and more significant, when P is less than 0.01. One often accepts the alternative hypothesis, (i.e. rejects a null hypothesis) if the p-value is less than 0.05 or 0.01, corresponding to a 5% or 1% chance respectively of rejecting the null hypothesis when it is true (Type I error).