TYPE I ERROR:
Also called an alpha error. A type I error is a false positive. You make this kind of error when you reject a null hypothesis when it is actually true.
TYPE II ERROR:
Also called a beta error. A type II error is a false negative. You make this kind of error when you fail to reject the null hypothesis when you should (i.e. when the ...
This solution explains the difference between Type I and Type II errors when testing a hypothesis and provides an example of each.