Discussion
The P-value in hypothesis testing represents which of the following :
Answer: D
The P-value is the probability of observing results as extreme or more extreme than currently observed, given that the null hypothesis is true.
It assumes the null hypothesis and asks how surprising the data are under it. A small P-value, below the chosen significance level such as 0.05, means such extreme results would rarely occur if the null hypothesis were true, so it is rejected.
The common misreadings are the other options. The P-value is not the probability that the null hypothesis is true, because it is computed assuming that it is true. It is not the probability of failing to reject the null, and it is not the probability that the results 'are significant'; significance is a decision made by comparing the P-value with the chosen level.
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