234 Using Lists & Spreadsheet
1-PropZTest (zTest_1Prop)
1-PropZTest (one-proportion z test) computes a test for an unknown
proportion of successes (prop). It takes as input the count of successes in
the sample x and the count of observations in the sample n. 1-PropZTest
tests the null hypothesis H
0
:prop=p
0
against one of the alternatives
below.
•H
a
: propƒp
0
(prop:ƒp0)
•H
a
: prop<p
0
(prop:<p0)
• H
a
: prop>p
0
(prop:>p0)
This test is useful in determining if the probability of the success seen in a
sample is significantly different from the probability of the population or
if it is due to sampling error, deviation, or other factors.
2-PropZTest (zTest_2Prop)
2-PropZTest (two-proportion z test) computes a test to compare the
proportion of successes (p
1
and p
2
) from two populations. It takes as
input the count of successes in each sample (
x
1
and x
2
) and the count of
observations in each sample (
n
1
and n
2
). 2-PropZTest tests the null
hypothesis H
0
:p
1
=p
2
(using the pooled sample proportion Ç) against one
of the alternatives below.
•H
a
: p
1
ƒp
2
(p1:ƒp2)
•H
a
: p
1
<p
2
(p1:<p2)
•
H
a
: p
1
>p
2
(p1:>p2)
This test is useful in determining if the probability of success seen in two
samples is equal.
c
2
GOF-Test
c
2
GOF-Test (Chi Square Goodness of Fit) performs a test to confirm that
sample data is from a population that conforms to a specified
distribution. For example, c
2
GOF can confirm that the sample data came
from a normal distribution.
c
2
-Test
c
2
-Test (chi-square test) computes a chi-square test for association on the
two-way table of counts in the specified Observed matrix. The null
hypothesis H
0
for a two-way table is: no association exists between row
variables and column variables. The alternative hypothesis is: the
variables are related.
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