A survey by Ipsos-Reid reported in American Demographics showed that if a person was given a $1,000 windfall, 36% would spend the money on home improvement, 24% on leisure travel/vacation, 15% on clothing, 15% on home entertainment or electronic products, and 10% on local entertainment including restaurants and movies. Suppose a researcher believes that these results would not be the same if posed to adults between 21 and 30 years of age. The researcher conducts a new survey interviewing 200 adults between 21 and 30 years of age asking these same questions. A chi-square goodness-of-fit test is conducted to compare the results of the new survey to the one taken by Ipsos Reid. The Excel results follow. The observed and expected values are for the categories as already listed and appear in the same order. Discuss the findings.
How did the distribution of results from the new survey compare to the old? Discuss the business implications of this outcome.
21–30 Years of Age ... General Population
Observed ....... Expected
36 ........... 72
64 ......... 48
42 ......... 30
38 ......... 30
20 .......... 20

The p-value for the chi-square goodness-of-fit test is: 0.0000043. The observed chi-square for the goodness-of-fit test is: 30.27.