104k views
14 votes
How do we interpret Type I and Type II errors?

User Paperhorse
by
6.1k points

1 Answer

3 votes

Answer:

In statistical hypothesis testing, a type I error is the rejection of a true null hypothesis (also known as a "false positive" finding or conclusion; example: "an innocent person is convicted"), while a type II error is the non-rejection of a false null hypothesis (also known as a "false negative" finding or conclusion ...

Hope it helps!!!

User Jerlam
by
5.1k points