Using the Wilcoxon Signed-Ranks Test. In Exercises 5–8, refer to the sample data for the given exercises in Section 13-2 on page 611. Use the Wilcoxon signed-ranks test to test the claim that the matched pairs have differences that come from a population with a median equal to zero. Use a 0.05 significance level.

Exercise 6 “Speed Dating: Attractiveness”

Short Answer

Expert verified

There is not enough evidence to conclude that the matched pairs of attractiveness ratings have differences that do not come from a population with a median equal to 0.

Step by step solution

01

Given information

Wilcoxon signed-rank test is the non-parametric counterpart of the t-test.

In reference to exercise 6 in section 13-2, the data of female attractiveness and male attractiveness ratings is given as shown below:

Rating of Male by Female

4

8

7

7

6

8

6

4

2

5

9.5

7

Rating of Female by Male

6

8

7

9

5

7

5

4

6

8

6

5

02

Define Wilcoxon signed-rank test

The Wilcoxon signed-rank test is the distribution-free test that can be used to analyze the difference between two samples that are matched on certain characteristics.

03

Identify the statistical hypotheses

The null hypothesis is as follows:

The matched pairs of attractiveness ratings have differences that come from a population with a median equal to 0.


The alternative hypothesis is as follows:

The matched pairs of attractiveness ratings have differences that do not come from a population with a median equal to 0.

04

Calculate the signed ranks

The signed ranks can be obtained as:

  • Compute the differences by subtracting the value in the second sample from the corresponding value in the first sample. The following table shows the differences along with their signs:

Rating of Male by Female

4

8

7

7

6

8

6

4

2

5

9.5

7

Rating of Female by Male

6

8

7

9

5

7

5

4

6

8

6

5

Sign of Difference

–2

0

0

–2

+1

+1

+1

0

–4

–3

+3.5

+2

  • Compute the ranks of absolute differences by sorting themfrom smallest to largest.
  • Assign the smallest observation the rank of 1, and increase the ranks until the largest observation.
  • Discard the values with a difference of 0.
  • If any of the observations are repeated, assign the mean value of the ranks to all those observations. The following table shows the ranks:

Rating of Male by Female

4

8

7

7

6

8

6

4

2

5

9.5

7

Rating of Female by Male

6

8

7

9

5

7

5

4

6

8

6

5

Difference

–2

0

0

–2

+1

+1

+1

0

–4

–3

+3.5

+2

Rank of |d|

5

\( \times \)

\( \times \)

5

2

2

2

\( \times \)

9

7

8

5

  • Assign the sign to the ranks according to the sign of the difference. The following table shows the sign of the ranks:

Rating of Male by Female

4

8

7

7

6

8

6

4

2

5

9.5

7

Rating of Female by Male

6

8

7

9

5

7

5

4

6

8

6

5

Difference

–2

0

0

–2

+1

+1

+1

0

–4

–3

+3.5

+2

Rank of |d|

5

\( \times \)

\( \times \)

5

2

2

2

\( \times \)

9

7

8

5

Signed-Ranks

–5

\( \times \)

\( \times \)

–5

+2

+2

+2

\( \times \)

–9

–7

+8

+5

05

Calculate the sum of ranks

Compute the sum of the positive ranks as shown below:

\(\begin{array}{c}Su{m_{positive}} = 2 + 2 + 2 + 8 + 5\\ = 19\end{array}\)

Compute the sum of the negative ranks and then calculate its absolute values.

\(\begin{array}{c}\left| {Su{m_{negative}}} \right| = \left| {\left( { - 5} \right) + \left( { - 5} \right) + \left( { - 9} \right) + \left( { - 7} \right)} \right|\\ = \left| { - 26} \right|\\ = 26\end{array}\)

06

Calculate the test statistic and the degrees of freedom

Consider the smaller sum as the test statistic.

Here, the smaller sum is 19.

Thus, T is equal to 19.

The critical value for n=12 and\(\alpha \)= 0.05 for a two-tailed test is equal to 14.

As the test statistic value is greater than the critical value, the null hypothesis fails to reject.

07

Draw a conclusion

There is not enough evidence to conclude that the matched pairs of attractiveness ratings have differences that do not come from a population with a median equal to 0.

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Most popular questions from this chapter

Efficiency Refer to Table 13-2 on page 600 and identify the efficiency of the Wilcoxon rank-sum test. What does that value tell us about the test?

Using Nonparametric Tests. In Exercises 1–10, use a 0.05 significance level with the indicated test. If no particular test is specified, use the appropriate nonparametric test from this chapter.

Airline Fares Refer to the same data from the preceding exercise. Use the Wilcoxon signed ranks test to test the claim that differences between fares for flights scheduled 1 day in advance and those scheduled 30 days in advance have a median equal to 0. What do the results suggest?

Matched Pairs.In Exercises 5–8, use the sign test for the data consisting of matched pairs.

Speed Dating: Attributes Listed below are “attribute” ratings made by couples participating in a speed dating session. Each attribute rating is the sum of the ratings of five attributes (sincerity, intelligence, fun, ambition, shared interests). The listed ratings are from Data Set 18 “Speed Dating” in Appendix B. Use a 0.05 significance level to test the claim that there is a difference between female attribute ratings and male attribute ratings.

Rating of Male by Female

29

38

36

37

30

34

35

23

43

Rating of Female by Male

36

34

34

33

31

17

31

30

42

Using Nonparametric Tests. In Exercises 1–10, use a 0.05 significance level with the indicated test. If no particular test is specified, use the appropriate nonparametric test from this chapter.

Job Stress and Income Listed below are job stress scores and median annual salaries (thousands of dollars) for various jobs, including firefighters, airline pilots, police officers, and university professors (based on data from “Job Rated Stress Score” from CareerCast.com). Do these data suggest that there is a correlation between job stress and annual income? Does it appear that jobs with more stress have higher salaries?

Stress

71.59

60.46

50.82

6.94

8.1

50.33

49.2

48.8

11.4

Median Salary

45.6

98.4

57

69

35.4

46.1

42.5

37.1

31.2

Sign Test vs. Wilcoxon Signed-Ranks Test Using the data in Exercise 1, we can test for no difference between body temperatures at 8 AM and 12 AM by using the sign test or the Wilcoxon signed-ranks test. In what sense does the Wilcoxon signed-ranks test incorporate and use more information than the sign test?

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