Question 1167501
.


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