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One Big Bill or Many Smaller Bills In a study of the 鈥渄enomination effect,鈥 150 women in China were given either a single 100 yuan bill or a total of 100 yuan in smaller bills. The value of 100 yuan is about $15. The women were given the choice of spending the money on specific items or keeping the money. The results are summarized in the table below (based on 鈥淭he Denomination Effect,鈥 by Priya Raghubir and Joydeep Srivastava, Journal of Consumer Research, Vol. 36). Use a 0.05 significance level to test the claim that the form of the 100 yuan is independent of whether the money was spent. What does the result suggest about a denomination effect?

Spent the Money

Kept the Money

Women Given a Single 100-Yuan Bill

60

15

Women Given 100 Yuan in Smaller Bills

68

7

Short Answer

Expert verified

There is not enough evidence to conclude that the form of currency received is not independent of whether the money was spent /kept.

The claim of a denomination effect is not supported by substantial evidence. Whether 100 yuan is in the shape of a single bill or multiple smaller notes appears to have little effect on Chinese women.

Step by step solution

01

Given information

A table is devised showing the number of women who spent/kept the money depending on whether they received a single bill or smaller bills.

02

Hypotheses

The null hypothesis is as follows:

The form of currency received is independent of whether the money was spent /kept.

The alternative hypothesis is as follows:

The form of currency received is not independent of whether the money was spent /kept.

It is a right-tailed test.

If the test statistic value is greater than the critical value, then the null hypothesis is rejected, otherwise not.

03

Determine the observed and expected frequencies

Observed Frequency:

The frequencies provided in the table are the observed frequencies. They are denoted by\(O\).

The following contingency table shows the observed frequency for each cell:


Spent the Money

Kept the Money

Women Given a Single 100-Yuan Bill

\({O_1}\)=60

\({O_2}\)=15

Women Given 100 Yuan in Smaller Bills

\({O_3}\)=68

\({O_4}\)=7

Expected Frequency:

The formula for computing the expected frequency for each cell is shown below:

\(E = \frac{{\left( {row\;total} \right)\left( {column\;total} \right)}}{{\left( {grand\;total} \right)}}\)

The row total for the first row is computed below:

\(\begin{aligned}{c}Row\;Tota{l_1} = 60 + 15\\ = 75\end{aligned}\)

The row total for the second row is computed below:

\(\begin{aligned}{c}Row\;Tota{l_2} = 68 + 7\\ = 75\end{aligned}\)

The column total for the first column is computed below:

\(\begin{aligned}{c}Column\;Tota{l_1} = 60 + 68\\ = 128\end{aligned}\)

The column total for the second column is computed below:

\(\begin{aligned}{c}Column\;Tota{l_2} = 15 + 7\\ = 22\end{aligned}\)

The grand total can be computed as follows:

\(\begin{aligned}{c}Grand\;Total = \left( {75 + 75} \right)\\ = \left( {128 + 22} \right)\\ = 150\end{aligned}\)

Thus, the following table shows the expected frequencies for each of the corresponding observed frequencies:


Spent the Money

Kept the Money

Women Given a Single 100-Yuan Bill

\[\begin{aligned}{c}{E_1} = \frac{{\left( {75} \right)\left( {128} \right)}}{{150}}\\ = 64\end{aligned}\]

\[\begin{aligned}{c}{E_2} = \frac{{\left( {75} \right)\left( {22} \right)}}{{150}}\\ = 11\end{aligned}\]

Women Given 100 Yuan in Smaller Bills

\[\begin{aligned}{c}{E_3} = \frac{{\left( {75} \right)\left( {128} \right)}}{{150}}\\ = 64\end{aligned}\]

\[\begin{aligned}{c}{E_4} = \frac{{\left( {75} \right)\left( {22} \right)}}{{150}}\\ = 11\end{aligned}\]

The table below shows the necessary calculations:

O

E

O 鈥 E

\({\left( {O - E} \right)^2}\)

\(\frac{{{{\left( {O - E} \right)}^2}}}{E}\)

60

64

-4

16

0.250

15

11

4

16

1.4545

68

64

4

16

0.250

7

11

-4

16

1.4545

04

Compute the test statistic, critical value and p-value

The test statistic is computed as shown below:

\[\begin{aligned}{c}{\chi ^2} = \sum {\frac{{{{\left( {O - E} \right)}^2}}}{E}\;\;\; \sim } {\chi ^2}_{\left( {r - 1} \right)\left( {c - 1} \right)}\\ = 0.25 + 1.4545 + 0.25 + 1.4545\\ = 3.409\end{aligned}\]

Thus,\({\chi ^2} = 3.409\).

Let r denote the number of rows in the contingency table.

Let c denote the number of columns in the contingency table.

The degrees of freedom are computed below:

\(\begin{aligned}{c}df = \left( {r - 1} \right)\left( {c - 1} \right)\\ = \left( {2 - 1} \right)\left( {2 - 1} \right)\\ = 1\end{aligned}\)

The critical value of\({\chi ^2}\)for 1 degree of freedom at 0.05 level of significance for a right-tailed test is equal to 3.8415.

The corresponding p-value is approximately equal to 0.0648.

05

Decision and conclusion of the test

Since the value of the test statistic is less than the critical value and the p-value is greater than 0.05, the null hypothesis fails to reject.

There is not enough evidence to conclude that the form of currency received is not independent of whether the money was spent /kept.

The claim of a denomination effect is not supported by substantial evidence. Whether 100 yuan is in the shape of a single bill or multiple smaller notes appears to have little effect on Chinese women.

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Most popular questions from this chapter

Probability Refer to the results from the 150 subjects in Cumulative Review Exercise 5.

a.Find the probability that if 1 of the 150 subjects is randomly selected, the result is a woman who spent the money.

b.Find the probability that if 1 of the 150 subjects is randomly selected, the result is a woman who spent the money or was given a single 100-yuan bill.

c.If two different women are randomly selected, find the probability that they both spent the money.

The table below includes results from polygraph (lie detector) experiments conducted by researchers Charles R. Honts (Boise State University) and Gordon H. Barland (Department of Defense Polygraph Institute). In each case, it was known if the subject lied or did not lie, so the table indicates when the polygraph test was correct. Use a 0.05 significance level to test the claim that whether a subject lies is independent of the polygraph test indication. Do the results suggest that polygraphs are effective in distinguishing between truths and lies?

Did the subject Actually Lie?


No (Did Not Lie)

Yes (Lied)

Polygraph test indicates that the subject lied.


15

42

Polygraph test indicates that the subject did not lied.


32

9

In a study of the 鈥渄enomination effect,鈥 43 college students

were each given one dollar in the form of four quarters, while 46 other college students were each given one dollar in the form of a dollar bill. All of the students were then given two choices: (1) keep the money; (2) spend the money on gum. The results are given in the accompanying table (based on 鈥淭he Denomination Effect,鈥 by PriyaRaghubir and Joydeep Srivastava, Journal of Consumer Research,Vol. 36.) Use a 0.05 significance level to test the claim that whether students purchased gum or kept the money is independent of whether they were given four quarters or a \(1 bill. Is there a 鈥渄enomination effect鈥?

Purchased Gum

Kept the Money

Students Given Four Quarters

27

16

Students Given a \)1 Bill

12

34

Questions 6鈥10 refer to the sample data in the following table, which describes the fate of the passengers and crew aboard the Titanic when it sank on April 15, 1912. Assume that the data are a sample from a large population and we want to use a 0.05 significance level to test the claim that surviving is independent of whether the person is a man, woman, boy, or girl.


Men

Women

Boys

Girls

Survived

332

318

29

27

Died

1360

104

35

18

Is the hypothesis test left-tailed, right-tailed, or two-tailed?

Motor Vehicle Fatalities The table below lists motor vehicle fatalities by day of the week for a recent year (based on data from the Insurance Institute for Highway Safety). Use a 0.01 significance level to test the claim that auto fatalities occur on the different days of the week with the same frequency. Provide an explanation for the results.

Day

Sun.

Mon.

Tues.

Wed.

Thurs.

Fri.

Sat.

Frequency

5304

4002

4082

4010

4268

5068

5985

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