Type-II error in Hypothesis Testing
Basically, it's called an error because you're making the wrong decision. Like for instance, let's say your null hypothesis is something like: The patient does not have cancer. And the Alternative: The patient does have cancer. A type 2 error in this regard would be like saying "Oh, this patient does not have cancer" while they actually do have cancer. We are FAILING to REJECT a FALSE null. So I guess the most simple way to explain this is, we aren't catching a mistake, and letting it slide by. Of course this isn't all there is to it, but it should help kind of show what a type 2 error is and why it's something you want to avoid.