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Interpreting r. In Exercises 5–8, use a significance level of A = 0.05 and refer to the accompanying displays.

5. Bear Weight and Chest Size Fifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in Data Set 9 “Bear Measurements” in Appendix B; results are shown in the accompanying Statdisk display. Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight?

Short Answer

Expert verified

There is enough evidence to support the claim that there is a linear correlation between weights and chest sizes.

The chest sizes are easier to be recorded than weights.

As weights and chest sizes are highly correlated, chest sizes can be used to predict weights.

Step by step solution

01

Given information

The level of significance is 0.05.

The output for the hypothesis test for correlation between weights of bears and chest sizes are known.

02

Hypothesis test for correlation between weights and chest size

Let\(\rho \)be the true correlation measure between the two variables; weights and chest sizes.

The hypotheses be formulated as follows:

\(\begin{array}{l}{H_o}:\rho = 0\\{H_a}:\rho \ne 0\end{array}\)

From the output the following measures are known,

\(\begin{array}{c}r = 0.963\\p{\rm{ - value}} = 0.000\end{array}\)

As the p-value is lesser than 0.05, the null hypothesis is rejected.

Thus, there is enough evidence at 0.05 level of significance to conclude that there is a significant correlation between the two variables; weight and chest sizeof bears.

03

Measurement of variables

Of the two measures, it is not easy to weigh the bears on a scale as they are too heavy to be lifted. On the other hand, the chest sizes are comparatively easier to be recorded for the bears in anethesized state.

04

Predict the measure of weight from chest size

The weight is highly correlated with the chest sizes, and hence the variable can be used to predict the weights.

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Most popular questions from this chapter

Coefficient of Determination Using the heights and weights described in Exercise 1, the linear correlation coefficient r is 0.394. Find the value of the coefficient of determination. What practical information does the coefficient of determination provide?

The following exercises are based on the following sample data consisting of numbers of enrolled students (in thousands) and numbers of burglaries for randomly selected large colleges in a recent year (based on data from the New York Times).

Exercise 1 stated that ris found to be 0.499. Does that value change if the actual enrollment values of 53,000, 28,000, 27,000, 36,000, and 42,000 are used instead of 53, 28, 27, 36, and 42?

The following exercises are based on the following sample data consisting of numbers of enrolled students (in thousands) and numbers of burglaries for randomly selected large colleges in a recent year (based on data from the New York Times).

Repeat the preceding exercise, assuming that the linear correlation coefficient is r= 0.997.

Testing for a Linear Correlation. In Exercises 13–28, construct a scatterplot, and find the value of the linear correlation coefficient r. Also find the P-value or the critical values of r from Table A-6. Use a significance level of A = 0.05. Determine whether there is sufficient evidence to support a claim of a linear correlation between the two variables. (Save your work because the same data sets will be used in Section 10-2 exercises.)

CPI and the Subway Use CPI>subway data from the preceding exercise to determine whether there is a significant linear correlation between the CPI (Consumer Price Index) and the subway fare.

Critical Thinking: Is the pain medicine Duragesic effective in reducing pain? Listed below are measures of pain intensity before and after using the drug Duragesic (fentanyl) (based on data from Janssen Pharmaceutical Products, L.P.). The data are listed in order by row, and corresponding measures are from the same subject before and after treatment. For example, the first subject had a measure of 1.2 before treatment and a measure of 0.4 after treatment. Each pair of measurements is from one subject, and the intensity of pain was measured using the standard visual analog score. A higher score corresponds to higher pain intensity.

Pain Intensity Before Duragesic Treatment

1.2

1.3

1.5

1.6

8

3.4

3.5

2.8

2.6

2.2

3

7.1

2.3

2.1

3.4

6.4

5

4.2

2.8

3.9

5.2

6.9

6.9

5

5.5

6

5.5

8.6

9.4

10

7.6










Pain Intensity After Duragesic Treatment

0.4

1.4

1.8

2.9

6

1.4

0.7

3.9

0.9

1.8

0.9

9.3

8

6.8

2.3

0.4

0.7

1.2

4.5

2

1.6

2

2

6.8

6.6

4.1

4.6

2.9

5.4

4.8

4.1










Matched Pairs The methods of Section 9-3 can be used to test a claim about matched data. Identify the specific claim that the treatment is effective, then use the methods of Section 9-3 to test that claim.

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