Understanding the significance of the P-value

The probability that a null-hypothesis will be rejected even if it is proven true is the p-value. When there is no difference between two measures, then the hypothesis is said to be a null-hypothesis.

For example, if there is a hypothesis that, in the game of football, every player who plays 90 minutes will also score a goal then the null hypothesis would be that there is no relation between the number of minutes played and the goals scored.

Another example would be a hypothesis that a person with blood group A will have higher blood pressure than the person with blood group B. In a null hypothesis, there will be no difference, that is, no relation between the blood type and the pressure.

The significance level is given by (α) and if the p-value is equal or less than it, then the null hypothesis is declared inconsistent or invalid. Such a hypothesis is rejected.

One-tailed and two-tailed test

The following diagram represents the two-tails being used...