Warning: foreach() argument must be of type array|object, bool given in /var/www/html/web/app/themes/studypress-core-theme/template-parts/header/mobile-offcanvas.php on line 20

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.

Short Answer

Expert verified

It is claimed that the drug Duragesic is effective in reducing pain.

Using the methods of 9-3, it can be concluded that there is enough evidence to support the claim that the drug Duragesic is effective in reducing pain.

Step by step solution

01

Given information

The pain intensities of a group of subjects are recorded before and after using the drug Duragesic.

02

Hypotheses

It is claimed that the drug Duragesic is effective in reducing pain.

The following hypotheses are noted:

Null Hypothesis: The mean value of the pain intensity before the treatment is equal to the mean value of the pain intensity after the treatment.

\({H_0}:{\mu _d} = 0\)

Alternative Hypothesis: The mean value of the pain intensity before the treatment is greater than the mean value of the pain intensity after the treatment.

\({H_1}:{\mu _d} > 0\)

Here,\({\mu _d}\)represents the population difference in the pain intensities before and after the treatment.

The test is right-tailed.

03

Differences in the values of each matched pair

The following table shows the differences in the pain intensities before and after the treatment:

Before treatment

After treatment

Differences

1.2

0.4

0.8

1.3

1.4

-0.1

1.5

1.8

-0.3

1.6

2.9

-1.3

8

6

2

3.4

1.4

2

3.5

0.7

2.8

2.8

3.9

-1.1

2.6

0.9

1.7

2.2

1.8

0.4

3

0.9

2.1

7.1

9.3

-2.2

2.3

8

-5.7

2.1

6.8

-4.7

3.4

2.3

1.1

6.4

0.4

6

5

0.7

4.3

4.2

1.2

3

2.8

4.5

-1.7

3.9

2

1.9

5.2

1.6

3.6

6.9

2

4.9

6.9

2

4.9

5

6.8

-1.8

5.5

6.6

-1.1

6

4.1

1.9

5.5

4.6

0.9

8.6

2.9

5.7

9.4

5.4

4

10

4.8

5.2

7.6

4.1

3.5

The number of pairs is equal to\(n = 31\).

The mean value of the differences is computed below:

\(\begin{aligned} \bar d &= \frac{{0.8 + \left( { - 0.1} \right) + ...... + 3.5}}{{31}}\\ &= 1.38\end{aligned}\)

The standard deviation of the differences is computed below:

\(\begin{aligned} {s_d} &= \sqrt {\frac{{\sum\limits_{i = 1}^n {{{({d_i} - \bar d)}^2}} }}{{n - 1}}} \\ &= \sqrt {\frac{{{{\left( {0.8 - 1.38} \right)}^2} + {{\left( {\left( { - 0.1} \right) - 1.38} \right)}^2} + ....... + {{\left( {3.5 - 1.38} \right)}^2}}}{{31 - 1}}} \\ &= 2.92\end{aligned}\)

The mean value of the differences for the population of matched pairs \(\left( {{\mu _d}} \right)\) is considered to be equal to 0.

04

Compute the test statistic, critical value and the p-value

The value of the test statistic is computed as shown:

\(\begin{array}{c}t = \frac{{\bar d - {\mu _d}}}{{\frac{{{s_d}}}{{\sqrt n }}}}\\ = \frac{{1.38 - 0}}{{\frac{{2.92}}{{\sqrt {31} }}}}\\ = 2.623\end{array}\)

The degrees of freedom are computed below:

\(\begin{array}{c}df = n - 1\\ = 31 - 1\\ = 30\end{array}\)

The critical value of t at\(\alpha = 0.05\)and degrees of freedom equal to 30 for a right-tailed test is equal to 1.6973.

The corresponding p-value is equal to 0.0068.

05

Decision and conclusion of the test

Since the value of the test statistic (2.623) is greater than the critical value and the p-value is less than 0.05, the null hypothesis is rejected.

There is enough evidence to conclude that the drug Duragesic is effective in reducing pain.

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with Vaia!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Stocks and Sunspots. Listed below are annual high values of the Dow Jones Industrial Average (DJIA) and annual mean sunspot numbers for eight recent years. Use the data for Exercises 1โ€“5. A sunspot number is a measure of sunspots or groups of sunspots on the surface of the sun. The DJIA is a commonly used index that is a weighted mean calculated from different stock values.

DJIA

14,198

13,338

10,606

11,625

12,929

13,589

16,577

18,054

Sunspot Number

7.5

2.9

3.1

16.5

55.7

57.6

64.7

79.3

z Scores Using only the sunspot numbers, identify the highest number and convert it to a z score. In the context of these sample data, is that highest value โ€œsignificantly highโ€? Why or why not?

Testing for a Linear Correlation. In Exercises 13โ€“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.)

22. Crickets and Temperature A classic application of correlation involves the association between the temperature and the number of times a cricket chirps in a minute. Listed below are the numbers of chirps in 1 min and the corresponding temperatures in ยฐF (based on data from The Song of Insects, by George W. Pierce, Harvard University Press). Is there sufficient evidence to conclude that there is a linear correlation between the number of chirps in 1 min and the temperature?

Actress

28

30

29

61

32

33

45

29

62

22

44

54

Actor

43

37

38

45

50

48

60

50

39

55

44

33

In Exercises 5โ€“8, we want to consider the correlation between heights of fathers and mothers and the heights of their sons. Refer to the

StatCrunch display and answer the given questions or identify the indicated items.

The display is based on Data Set 5 โ€œFamily Heightsโ€ in Appendix B.

Identify the following:

a. The P-value corresponding to the overall significance of the multiple regression equation

b. The value of the multiple coefficient of determination\({R^2}\).

c. The adjusted value of \({R^2}\)

Exercises 13โ€“28 use the same data sets as Exercises 13โ€“28 in Section 10-1. In each case, find the regression equation, letting the first variable be the predictor (x) variable. Find the indicated predicted value by following the prediction procedure summarized in Figure 10-5 on page 493.

Use the foot lengths and heights to find the best predicted height of a male

who has a foot length of 28 cm. Would the result be helpful to police crime scene investigators in trying to describe the male?

In Exercises 5โ€“8, we want to consider the correlation between heights of fathers and mothers and the heights of their sons. Refer to the

StatCrunch display and answer the given questions or identify the indicated items.

The display is based on Data Set 5 โ€œFamily Heightsโ€ in Appendix B.

A son will be born to a father who is 70 in. tall and a mother who is 60 in. tall. Use the multiple regression equation to predict the height of the son. Is the result likely to be a good predicted value? Why or why not?

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.

Sign-up for free