P-value

A p-value measures how well your data agree with the null hypothesis: a small p-value means the observed result would be surprising if the null were true, which counts as evidence against it. It is a probability about the data, not the probability that the null hypothesis is true. For example, a p-value of 0.02 says that if the null hypothesis held, data at least this extreme would occur about 2% of the time. You reject the null hypothesis when the p-value is at or below the significance level $\alpha$ (the Greek letter alpha).