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(a)
To find: Type of chi square to be used.
(a)
![Check Mark](/static/check-mark.png)
Answer to Problem 4CRE
Chi square test of association will be used.
Explanation of Solution
Given information:
Total number of people
The two way table of gender and sexual classification is as follows
Readers | |||
Men | Female | General | |
Sexual | |||
Not sexual |
Chi square test of association is used where the concern is to check the independency between two variables or any kind of relation or association.
Chi square goodness of fit is to test the fit of a certain distribution to the data.
Here, only one variable can be used.
As the data in the question randomly selected, have two variables and the concern is to check the association so, chi square test for association will be used.
(b)
To find: The null and the alternate hypotheses
(b)
![Check Mark](/static/check-mark.png)
Answer to Problem 4CRE
Explanation of Solution
The null hypothesis is the natural one and is the one on the assumption of which the test statistic is calculated.
As the chi square test of association will be used so,
The null hypothesis will be that the gender of audience and the sexuality of the magazine ads are independent.
The alternate hypothesis will be that the gender of audience and the sexuality of the magazine ads are not independent.
(c)
(c)
![Check Mark](/static/check-mark.png)
Explanation of Solution
Calculation:
Total number of women readers = number of sexual ads read by women
For
The percentage of not sexual ads among the women readers can be calculated as follows
For
The sum total not sexual will be
The expected count for not sexual women cell will be
For
The contribution of the not sexual women reader cell to chi statistic will be
Observed value
So,
(d)
To find: The conclusion based on the results given.
(d)
![Check Mark](/static/check-mark.png)
Answer to Problem 4CRE
The gender of the audience and the sexuality of the ads are not independent
Explanation of Solution
Given information:
Chi square value
P value
Concept used:
Reject null hypothesis if P value is less than the level of significance.
Here, assume the level of significance as
So,
Conclusion:
Using the above concept, there is sufficient evidence to reject null hypothesis at
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