Type I and Type II Errors Flashcards
1
Q
what is a type I error?
A
when the alternative hypothesis is accepted when it should’ve been the null hypothesis
- known as optimistic error or a false positive
2
Q
what is a type II error?
A
when the null hypothesis is accepted but it should be alternative hypothesis as in reality is true
- known as a pessimistic error or false negative
3
Q
what is the percent that the wrong hypothesis is accepted?
A
5%
4
Q
when are we more likely to make a type I error?
A
if significance level is too lenient, too high
- e.g 10% instead of 5%`
5
Q
when are we more likely to make a type II error?
A
if significance level is too stringent, too low
- e.g. 1% instead of 5%