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AP STATISTICS: CHAPTER 21
More About Tests and Intervals: Notes
If we use the results of a significance test to make a
decision, then we either reject the null hypothesis in
favor of the alternative hypothesis, or we fail to reject
the null hypothesis.
We hope that our decision will be correct, but it is
possible that we make the wrong decision. There are
two ways to make a wrong decision:
We can reject the null hypothesis when in fact it is
true. This is called a Type I Error .
 We can fail to reject the null hypothesis when in fact it
is false. This is called a Type II Error .

Truth about the population
Decision
based on
sample
H0 is TRUE
H0 is FALSE
REJECT H0
Type I Error
p=a
Correct Decision
(Power)
p=1–b
FAIL TO REJECT H0
Correct
Decision
Type II Error
p=b
We are interested in knowing the probability of
making a Type I Error and the probability of
making a Type II Error.
A Type I Error occurs if we reject the null
hypothesis when it is in fact true .
When do we reject the null hypothesis?
When we assume that it is true and find that the
statistic of interest falls within the rejection
region . The probability that the statistic falls
in the rejection region is the area of the shaded
region, or a .
Therefore the probability of a Type I Error is equal
to the significance level a of a fixed level test.
The probability that the test will reject the null
hypothesis H0 when in fact H0 is true is a .
A Type II Error occurs if we fail to reject the null
hypothesis when it is in fact false .
When do we fail to reject the null hypothesis?
When we assume that it is true and find that the
statistic of interest falls outside the rejection
region .
However, the probability that the statistic falls
outside the rejection region is NOT the area of the
unshaded region. Think about it… If the null
hypothesis is in fact false, then the picture is NOT
CORRECT… it is off center.
To calculate the probability of a Type II Error, we must find the probability
that the statistic falls outside the rejection region (the unshaded area)
given that the mean is some other specified value.
The probability of a Type II Error tells us the
probability of failing to reject the null
hypothesis when it is actually false . The
complement of this would be the probability of
rejecting the null hypothesis when it is actually
false. To calculate the probability of rejecting the
null hypothesis when it is actually false, compute
1 – P(Type II Error). This is called the power
of a significance test.
Ho: x = the right person for me
Ha: x = not the right person for me
H0 is TRUE
H0 is FALSE
REJECT H0
Unhappily
single (Type I
Error)
Happily single
FAIL TO REJECT H0
Happily
1?1?
married
Unhappily
Married (Type II
Error)
Airport Scanners:
Ho: x = the person is harmless (is not a terrorist)
Ha: x = the person is not harmless (is a terrorist)
H0 is TRUE
H0 is FALSE
REJECT H0
False Alarm
(Type I Error)
Terrorist is
caught
FAIL TO REJECT H0
Everybody is
happy
A Miss (Type II
Error)