The probability value – or p-value – helps us decide whether or not the null hypothesis should be rejected.

There are some common misunderstandings about p-values. The p-value is not:

• … the probability that the null hypothesis is true.
• … the probability that the alternative hypothesis is false.
• … the probability of the occurrence of a type I error (falsely rejecting H₀).
• … the probability that replicating the experiment would yield the same conclusion.
• … the probability that the finding is a “fluke”.
• … an indicator of the size of the effect or importance of the findings.
• … determining the significance level.

Using the p-value to make this decision of whether or not to reject the null hypothesis, it must first be decided what probability value we find acceptable. This is often referred to “significance level”.

If the p-value is below this level, it means that we can reject the null hypothesis in favour of the alternative hypothesis.

If the p-value is above this level, it means that we cannot reject the null hypothesis.

Note The smaller the p-value, the more convincing is the rejection of the null hypothesis.