Download Identifying type 1 and type 2 errors – example: The... Screen 1

Ch 8 Type I and Type II Errors
Screen 1
Identifying type 1 and type 2 errors – example: The hypothesis is – the proportion of college grads who smoke
is less than 27/100. Recall that the null hypothesis would be ‘p = 27/100’s’ and the alternative hypothesis would
be ‘p’ < 27/100’s. Now, the type-1 error occurs when the sample data leads you to reject a true null hypothesis,
so for this example the type one error is the sample data supports the claim that ‘p’ < 27/100’s when in truth ‘p’
is 27/100’s.
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Recall that the type 2 error occurs when your sample data leads you to reject a false null. So for this example
the type-II error is the sample data does not lead you to reject that p = 27/100’s when, in truth, p < 27/100. Note
that we cannot know if a type-I or type-II error occurs, but we can discuss the probability of each occurring. We
let alpha equal the probability of a type-I error occurring, and beta = the probability of a type-II error occurring.
We call alpha the significance level of the test, and beta is discussed in advanced statistics courses.