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Since the p-value of .016 is less than the significance level of .05 we reject the null hypothesis
that row and column variables are independent. We have evidence that gender does influence
opinions concerning school discipline.
The see the expected frequencies
Press the 2
nd
key and then the x
-1
key.
Press the ► key twice to get to EDIT.
Press the number 2 key to get to [B].
Comparisons such as 70 men were against giving more freedom to teachaers to punish kids and
we only expected 59.5 of them to be against it if the variables are really independent.
Example: Gender and Cell Phones
A researcher wanted to study the relationship between gender and owning cell phones. She took
a sample of 2000 adults and obtained the information given in the following table.
Own Cell Phone Do Not Own Cell Phone
Men 640 450
Women 440 470
Test at a 1% level of significance whether or not gender and owning cell phones are independent.
Then check the expected frequencies for any possible practical significant differences between
the associated observed and expected frequencies.
Remember the data has to be stored differently than in previous statistical test on the calculator.
The data for a Chi-Square test of independence has to be stored in a Matrix.
Press the 2
nd
key and then the x
-1
key to get to MATRX.
Press the ► key twice to highlight EDIT.
Press the ENTER key.
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