If the null-hypothesis is true, the P-value
(probability value) of a hypothesis test is the
probability of obtaining a sample statistic
with a value as extreme or more extreme
than the one determined from the sample
data (farther away).
The smaller the P-Value, the more evidence
there is to reject the null hypothesis.
A very small P-Value indicates a rare
occurrence.
If the P-Value ≤ α, then you will reject the
null hypothesis.
If the P-Value > α, then you will fail to reject
the null hypothesis.
◦ If Ha contains <, the test is a left-tailed test.
P is the area to the left of the test statistic.
◦ If Ha contains >, the test is a right-tailed test.
P is the area to the right of the test statistic.
◦ If Ha contains ≠, the test is a two-tailed test.
P is the area to the left of the negative test statistic,
and P is the area to the right of the positive test
statistic.
Hypothesis tests for proportions occur (for
example) when a politician wants to know the
proportion of his or her constituents who favor a
certain bill or when a quality assurance engineer
tests the proportion of parts which are defective.
Z-Test for a Proportion P: A statistical test for a
population proportion P. It can be used when
np ≥ 5 and nq ≥ 5. (q is 1-p)
A test statistic is the sample proportion p-hat.
The standardized test statistic is z…formula to
follow later.
1.
2.
3.
4.
Verify that np ≥ 5 and nq ≥ 5. If these are
true, the distribution for p-hat will be
normal and you can continue; otherwise you
cannot use normal distribution for the
problem.
State the claim…Identify null and alternative
hypotheses.
Specify the level of significance (α).
Sketch the sampling distribution (make a
curve).
5.
6.
Determine any critical values (see next
slide). These will be borders between
rejection regions and non-rejection regions
(below). They will be the same values each
time.
Determine any rejection regions. These are
a range of values for which the Ho is not
probable. If a test statistic falls into this
region, Ho is rejected. A critical value
separates the rejection region from the
non-rejection region.
Tailed
Significance Level
Critical Value
Left
0.10
-1.28
Right
0.10
1.28
Two
0.10
±1.645
Left
0.05
-1.645
Right
0.05
1.645
Two
0.05
±1.96
Left
0.01
-2.33
Right
0.01
2.33
Two
0.01
±2.575
7.
8.
9.
Find the z-score (standard score):
Make a decision to
reject or fail to reject
Ho.
pˆ p
z
pq
n
Interpret the decision
in the context of the original claim.
A medical researcher claims that less than
20% of adults in the U.S. are allergic to a
medication. In a random sample of 100
adults, 15% say they have such an allergy. At
α = 0.01, is there enough evidence to
support the researcher’s claim?
n = 100, p = 0.20, q = 0.80
1. np = 20, nq = 80…you can continue.
2. Ho: p ≥ 0.2, Ha: p < 0.2
Since Ha is <, this is a left-tailed test, and
since α = 0.01, we will be using the critical
value as -2.33 (they use the symbol zo for
this).
See drawing on board for sketch.
The rejection region is z < -2.33.
The standardized test statistic (z) is:
0.15 0.2
z
1.25
(0.2)(0.8)
100
Since z = -1.25, and this is not in the
rejection region, you should decide not to
reject the null hypothesis.
Interpretation: There is not enough evidence
to support the claim that less than 20% of
adults in the U.S. are allergic to the
medication.
USA Today reports that 5% of US adults have
seen an extraterrestrial being. You decide to
test this claim and ask a random sample of
250 U.S. adults whether they have ever seen
an extraterrestrial being. Of those surveyed
8% reply yes. At α = 0.01, is there enough
evidence to reject the claim?
Your group is to complete and document all
the steps to come to the final answer. This
will be turned in.
There
will be some
on Friday