p-value and relation to error


TS Contributor
The p-value is the probability that the test statistic takes on its current value or larger, if in fact Ho (the null hypothesis) is true.

Before conducting the experiment or collecting data, you set an alpha level, or the amount of risk you're willing to take on (the probability that you incorrectly reject Ho - otherwise known as Type I error).

If the p-value is less than alpha, then there is sufficient evidence to reject Ho - in other words, the likelihood that Ho is true is less than your risk tolerance.