Question 1167501: Define:Type I and Type II Errors
Answer by ikleyn(52803)   (Show Source):
You can put this solution on YOUR website! .
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.
See this Wikipedia article
https://en.wikipedia.org/wiki/Type_I_and_type_II_errors#:~:text=In%20statistical%20hypothesis%20testing%2C%20a,false%20negative%22%20finding%20or%20conclusion
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