p-value

Shows you the probability that you are wrong in case you reject the null hypothesis. (cause it is actually right)

Example 1:

Eg. You have a p-value of 4%.

That means if you reject the null hypothesis you will make a mistake with a probability of 4%.

Example 2:

Eg. You have a p-value of 40%

That means if you reject the null hypothesis you will make a mistake with a probability of 40%.

Now you can compare the p-value with your level of significance (alpha).

Let’s say we have an alpha of 10% (confidence interval of 90%). Further, we have a p-value of 4%. The level of significance tells us we are allowed to be wrong in max. 10% of cases if we reject the null hypothesis. The p-value is below that amount. So we can reject the null hypothesis.