9.2 Critical Values for Statistical Significance in ...
[Pages:17]9.2 Critical Values for Statistical Significance in
Hypothesis testing
1
Step 3 of Hypothesis Testing
n Step 3 involves computing a probability, and for this class, that means using the normal distribution and the z-table in Appendix A.
n What normal distribution will we use?
?For p ?
? ?For ?
2
Step 3:
n What normal distribution?
?For a hypothesis test about ? , we will
use...
We plug-in s here as our estimate for .
X ~ N (?x = ?0, ! x = !
) n
We assume the null is true, so we put the stated
value of from the null hypothesis here.
3
Step 3:
n What normal distribution?
?For a hypothesis test about p, we will
use...
"
p^ ~ N $ p0,
#
p0
(1
!
p0
)
% '
n&
We assume the null is true, so we put the stated
value of p from the null hypothesis into the
formula for the mean and standard deviation.
4
Book example (Section 9.2, p.380):
n The null and alternative hypotheses are H0: ? = $39,000 Ha: ? < $39,000 (one-sided test)
Data summary:
n=100 x = $37, 000
s=$6,150
5
Test of Hypothesis for ?
n Step 3: What normal distribution?
X ~ N (?x = ?0, ! x = !
) n
null hypothesis assumed true
X ~ N (?x = $39, 000, ! x = $6,150
) 100
6
From this normal distribution we can compute a z-score
z = 37, 000 ! 39, 000 = !3.25
for our x = $37, 000 :
6,150 / 100
$37,000
The observed sample mean of $37,000 is 3.25 standard deviations below the claimed mean.
7
What z-score could I get that will make me reject H0:=0?
n It would have to be something in the `tail' of the z-distribution (i.e. something far from the assumed true mean 0).
n It would have to suggest that my observed data is unlikely to occur under the null being true (small P-value).
n What about z=4? What about z=2?
8
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