Do you know how to interpret the p-value? Let’s revisit the null hypothesis, which is the hypothesis that we assume unless there is reasonable doubt or evidence to reject it. In this case, we can use the p-value as our evidence. Usually we compare the p-value with 0.05 or 5%. This is called the level of significance which is denoted with the variable α (alpha).
If the p-value is lesser than alpha, we have to reject the null hypothesis. If it is greater than the alpha, we fail to reject the null hypothesis. If the p-value is equal or nearly similar to the alpha, it depends on the statistician to reject or fail to reject the null hypothesis as the p-value depends on the quality of your experiment. However it is probably better to repeat the experiment to be sure. This is why we do not say “accept the null hypothesis”. We cannot really accept it as the results depend simply on the experiment’s quality. If the p value is larger than alpha, the evidence just tells us that it is not sufficient enough for us to reject it- there can still be uncertainty that it could be rejected.
Remember:
The p-value can tell us whether to reject or fail to reject the null hypothesis.
If the p-value is lesser than alpha, we have to reject the null hypothesis. Otherwise, we fail to reject it.
We cannot accept the null hypothesis as the results depend on the quality of our experiments.
Tanim Talino 