Statistical tests separate significant effects from mere luck or random chance.
All hypothesis tests have unavoidable, but quantifiable, risks of making the wrong conclusion.
The Type I risk is the chance of deciding that a significant effect is present when it isn't. The Type II risk is the chance of not detecting a significant effect when one exists. Every statistical test tests the null hypothesis H 0 against the alternate hypothesis H 1 . The process change or treatment makes no difference, or the process is operating properly. The null hypothesis is like presumption of innocence.