Texas Instruments TI-NSPIRE Software Manual page 246

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