Type I and II errors (1 of 2)
There
are two kinds of errors that can be made in
significance testing: (1) a true
null
hypothesis can be incorrectly rejected and (2) a false null
hypothesis can fail to be rejected. The former error is called a Type
I error and the latter error is called a Type II error. These two
types of errors are defined in the table.
Statistical Decision |
True State of the Null Hypothesis |
H_{0} True |
H_{0} False |
Reject H_{0} |
Type I error |
Correct |
Do not Reject H_{0} |
Correct |
Type II error |
The probability of a Type I
error is designated by the Greek letter alpha (
a) and is
called the Type I error rate; the probability of a Type II error (the
Type II error rate) is designated by the Greek letter beta (ß)
. A Type II error is only an error in the sense that an opportunity
to reject the null hypothesis correctly was lost. It is not an error
in the sense that an incorrect conclusion was drawn since no
conclusion is drawn when the
null hypothesis is
not rejected.