Compute Using: Data provided in the problem to the left and the Chi-Square Calculator to the left.

A sample of 500 shoppers was selected in a large metropolitan area to collect information concerning consumer behavior. Among the questions asked was, "Do you enjoy shopping for clothing?" The results are summarized in the table to the left.

1. Is there evidence of a significant difference between the proportion of males and females who

enjoy shopping for clothing at the 0.01 level of significance?

a. State the decision rule

b. Report the test statistic

c. Reporting your findings/results of your data analysis.

2. Determine the p-value and interpret its meaning.

3. If 206 males enjoyed shopping for clothing and 34 did not, is there evidence of a significant difference between the proportion of males and females who enjoy shopping for clothing at the 0.01 level of significance?

4. If 206 males enjoyed shopping for clothing and 34 did not, determine the p-value and interpret its meaning.

5. If you were an organizational consultant for the business who conducted this survey, how would you use these data in an organizational diagnosis? What additional information would you want to know to complete the organizational diagnosis and make a project improvement recommendation? Explain the importance of the given and additional needed information.

Chi-Square Test Calculator
Observed Frequencies
	Call to Action Button			Calculations
Enjoy?	Male	Female	Total		fo-fe
Yes	136	224	360		-36.8000	36.8000
No	104	36	140		36.8000	-36.8000
Total	240	260	500
Expected Frequencies
	Call to Action Button
Enjoy?	Male	Female	Total		(fo-fe)^2/fe
Yes	172.8000	187.2000	360		7.8370	7.2342
No	67.2000	72.8000	140		20.1524	18.6022
Total	240	260	500
Data
Level of Significance	0.01
Number of Rows	2
Number of Columns	2
Degrees of Freedom	1
Results
Critical Value	6.6349
Chi-Square Test Statistic	53.8258
p-Value	0.00000000
Reject the null hypothesis