The p-value provides an estimate of how often we would get the obtained result by chance if in fact, the null hypothesis is true.

The P-value approach involves determining “likely” or “unlikely” by determining the probability — assuming the null hypothesis were true — of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed. If the P-value is small, say less than (or equal to) α, then it is “unlikely.” And, if the P-value is large, say more than α, then it is “likely.”

If the P-value is less than (or equal to) α, then the null hypothesis is rejected in favor of the alternative hypothesis. And, if the P-value is greater than α, then the null hypothesis is not rejected.