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

Speed Dating: Attractiveness Listed below are “attractiveness” ratings (1 = not attractive; 10 = extremely attractive) made by couples participating in a speed dating session. The listed ratings are from Data Set 18 “Speed Dating”. Use a 0.05 significance level to test the claim that there is a difference between female attractiveness ratings and male attractiveness ratings.

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

Short Answer

Expert verified

There is not enough evidence to conclude that there is a difference between female and male attractiveness ratings.

Step by step solution

01

Given information

The two samples of data are given ratings of male attractiveness and female attractiveness.

02

Define sign test and frame the statistical hypothesis

The sign test belongs to the non-parametric (or distribution-free) category used to test the claim of difference between male and female attractiveness ratings.

Null hypothesis: There is no difference between male and female attractiveness ratings.

Alternative hypothesis: There is a difference between male and female attractiveness ratings.

The test is two-tailed.

03

Define sign of difference

If the male rating value is greater than the female rating, the sign of difference is positive.

If the male rating value is less than the female rating, the sign of difference is negative.

If the value of the Male rating is equal to the Female rating, the difference is zero.

The sign of the difference table is as follows:

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

-

0

0

-

+

+

+

0

-

-

+

+

The number of positive signs is equal to 5.

The number of negative signs is equal to 4.

The number of ties is equal to 3.

The sample size (n) is equal to 12.

04

Calculate the test statistic

Since n is less than 25, the test statistic value (x) is the number of times the less frequent sign occurs.

The less frequent sign is the negative sign, and it occurs four times.

Thus, x = 4.

05

Determine the result and conclusion of the test

From Table A-7, the critical value of x for n=12 and\(\alpha \)=0.05 for a two-tailed test equals 2.

Since the calculated value of x equal to 2 is greater than the critical value of 1, the null hypothesis is failed to reject.

There is not enough evidence to conclude that there is a difference between female and male attractiveness ratings.

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Most popular questions from this chapter

Mean and Median In a recent year, the players on the New York Yankees baseball team had salaries with a mean of \(7,052,129 and a median of \)2,500,000. Explain how the mean and median can be so far apart.

Level of Measurement Which of the levels of measurement (nominal, ordinal, interval, ratio) describe data that cannot be used with the methods of rank correlation? Explain.

Radiation in Baby Teeth Listed below are amounts of strontium-90 (in millibecquerels, or mBq, per gram of calcium) in a simple random sample of baby teeth obtained from Pennsylvania residents and New York residents born after 1979 (based on data from “An Unexpected Rise in Strontium-90 in U.S. Deciduous Teeth in the 1990s,” by Mangano et al., Science of the Total Environment). Use a 0.05 significance level to test the claim that the median amount of strontium-90 from Pennsylvania residents is the same as the median from New York residents.

Pennsylvania

155

142

149

130

151

163

151

142

156

133

138

161

New York

133

140

142

131

134

129

128

140

140

140

137

143

Using the Kruskal-Wallis Test. In Exercises 5–8, use the Kruskal-Wallis test.

Correcting the H Test Statistic for Ties In using the Kruskal-Wallis test, there is a correction factor that should be applied whenever there are many ties: Divide H by

\(1 - \frac{{\sum T }}{{{N^3} - N}}\)

First combine all of the sample data into one list, and then, in that combined list, identify the different groups of sample values that are tied. For each individual group of tied observations, identify the number of sample values that are tied and designate that number as t, then calculate\(T = {t^3} - t\). Next, add the T values to get\(\sum T \). The value of N is the total number of observations in all samples combined. Use this procedure to find the corrected value of H for Example 1 in this section on page 628. Does the corrected value of H differ substantially from the value found in Example 1?

Cell Phones and Crashes: Analyzing Newspaper Report In an article from the Associated Press, it was reported that researchers “randomly selected 100 New York motorists who had been in an accident and 100 who had not been in an accident. Of those in accidents, 13.7 percent owned a cellular phone, while just 10.6 percent of the accident-free drivers had a phone in the car.” What is wrong with these results?

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