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Testing Claims About Proportions. In Exercises 7–22, test the given claim. Identify the null hypothesis, alternative hypothesis, test statistic, P-value or critical value(s), then state the conclusion about the null hypothesis, as well as the final conclusion that addresses the original claim.

Clinical Trials of OxyContin OxyContin (oxycodone) is a drug used to treat pain, butit is well known for its addictiveness and danger. In a clinical trial, among subjects treatedwith OxyContin, 52 developed nausea and 175 did not develop nausea. Among other subjectsgiven placebos, 5 developed nausea and 40 did not develop nausea (based on data from PurduePharma L.P.). Use a 0.05 significance level to test for a difference between the rates of nauseafor those treated with OxyContin and those given a placebo.

a. Use a hypothesis test.

b. Use an appropriate confidence interval.

c. Does nausea appear to be an adverse reaction resulting from OxyContin?

Short Answer

Expert verified

a.There is not sufficient evidence to concludethat there is a significant difference between the rates of nausea for subjects who were treated with OxyContin and subjects who were given a placebo.

b.The 95% confidence interval is equal to (0.011, 0.225), andsince 0 is not included in the interval, it is concluded that there is a difference between the rates of nausea for subjects treated with OxyContin and subjects given a placebo.

c.Nausea appears to be an adverse reaction resulting from OxyContin.

Step by step solution

01

Given information

In a clinical trial, 52 subjects developed nausea, and 175 did not develop nausea among the subjects who were treated with OxyContin.

Also, among the subjects who were given placebos, fivedeveloped nausea, and 40 did not develop nausea.

02

Describe the hypothesis to be tested.

Null hypothesis:There is no difference between the rates of nausea for subjectswho were treated with OxyContin and subjectswho were given a placebo.

\({H_0}:{p_1} = {p_2}\)

Alternate hypothesis:There is a significant difference between the rates of nausea for subjectswho were treated with OxyContin and subjectswho were given a placebo.

\({\rm{ }}{H_1}:{p_1} \ne {p_2}\)

03

Calculate the sample statistics

Let\({n_1}\)and\({n_2}\)be the number ofsubjectstreated with OxyContin and the number of subjectsgiven a placebo, respectively.

The sample size\(\left( {{n_1}} \right)\)is computed below:

\(\begin{array}{c}{n_1} = 52 + 175\\ = 227\end{array}\)

The sample size\(\left( {{n_2}} \right)\)is computed below:

\(\begin{array}{c}{n_2} = 5 + 40\\ = 45\end{array}\)

Assume that\({x_1}\)and\({x_2}\)are the number ofsubjects who developed nausea and were given OxyContin and placebo, respectively.

Let \({\hat p_1}\)be the sample proportionof subjects who developed nausea and were treated with OxyContin.

\(\begin{array}{c}{{\hat p}_1} = \frac{{{x_1}}}{{{n_1}}}\\ = \frac{{52}}{{227}}\\ = 0.229\end{array}\)

\(\begin{array}{c}{{\hat q}_1} = 1 - {{\hat p}_1}\\ = 1 - 0.229\\ = 0.771\end{array}\)

Let \({\hat p_2}\)be the sample proportion ofsubjects who developed nausea and were given a placebo.

\(\begin{array}{c}{{\hat p}_2} = \frac{{{x_2}}}{{{n_2}}}\\ = \frac{5}{{45}}\\ = 0.111\end{array}\)

\(\begin{array}{c}{{\hat q}_2} = 1 - {{\hat p}_2}\\ = 1 - 0.111\\ = 0.889\end{array}\)

The value of the pooled sample proportion is equal to:

\(\begin{array}{c}\bar p = \frac{{{x_1} + {x_2}}}{{{n_1} + {n_2}}}\\ = \frac{{52 + 5}}{{227 + 45}}\\ = 0.210\end{array}\)

Hence,

\(\begin{array}{c}\bar q = 1 - \bar p\\ = 1 - 0.210\\ = 0.790\end{array}\)

04

Compute the value of the test statistic

The test statistic is equal to:

\(\begin{array}{c}z = \frac{{\left( {{{\hat p}_1} - {{\hat p}_2}} \right) - \left( {{p_1} - {p_2}} \right)}}{{\sqrt {\frac{{\bar p\bar q}}{{{n_1}}} + \frac{{\bar p\bar q}}{{{n_2}}}} }}\\ = \frac{{\left( {0.229 - 0.111} \right) - 0}}{{\sqrt {\frac{{\left( {0.210} \right)\left( {0.790} \right)}}{{227}} + \frac{{\left( {0.210} \right)\left( {0.790} \right)}}{{45}}} }}\\ = 1.776\end{array}\)

Referring to the standard normal distribution table, the critical values of z corresponding to\(\alpha = 0.05\)for a two-tailed test are -1.96 and 1.96.

Referring to the standard normal distribution table, the corresponding p-value is equal to 0.0757.

Here, the value of the test statistic lies between the two critical values, and the p-value is greater than 0.05.

Therefore, the null hypothesis is failed to reject.

05

Conclusion of the Test

a.

There is not sufficient evidence to concludethat there is a significant difference between the rates of nausea for subjectswho were treated with OxyContin and subjectswho were given a placebo.

06

Describe the confidence interval

If the level of significance for a two-tailed test is equal to 0.05, then the corresponding confidence level to construct the confidence interval is equal to 95%.

The expression for computing the confidence interval is given below:

\(\left( {{{\hat p}_1} - {{\hat p}_2}} \right) - E < {p_1} - {p_2} < \left( {{{\hat p}_1} - {{\hat p}_2}} \right) + E\)

07

Calculate the margin of error

E is the margin of error and has the following formula:

\(\begin{array}{c}E = {z_{\frac{\alpha }{2}}}\sqrt {\frac{{{{\hat p}_1}{{\hat q}_1}}}{{{n_1}}} + \frac{{{{\hat p}_2}{{\hat q}_2}}}{{{n_2}}}} \\ = 1.96 \times \sqrt {\frac{{\left( {0.229} \right)\left( {0.771} \right)}}{{227}} + \frac{{\left( {0.111} \right)\left( {0.889} \right)}}{{45}}} \\ = 0.1069\end{array}\)

08

Construct the confidence interval

b.

Substituting the required values, the following confidence interval is obtained:

\(\begin{array}{c}\left( {{{\hat p}_1} - {{\hat p}_2}} \right) - E < {p_1} - {p_2} < \left( {{{\hat p}_1} - {{\hat p}_2}} \right) + E\\(0.229 - 0.111) - 0.1069 < {p_1} - {p_2} < (0.229 - 0.111) + 0.1069\\0.011 < {p_1} - {p_2} < 0.225\end{array}\)

Thus, the 95% confidence interval is equal to (0.011, 0.225).

This confidenceinterval does not contain zero,which means that there is a significant difference between the two proportions of subjects who developed nausea.

Therefore, there is sufficient evidence to conclude thatthere is a significant difference between the rates of nausea for subjects who were treated with OxyContin and subjects who were given a placebo.

09

Examining nausea as an adverse reaction

c.

The sample results show that 22.9% of the subjects who were treated with OxyContin developed nausea.

Since the proportion is high, it can be said that nausea is an adverse reaction of OxyContin.

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Most popular questions from this chapter

In Exercises 5–20, assume that the two samples are independent simple random samples selected from normally distributed populations, and do not assume that the population standard deviations are equal. (Note: Answers in Appendix D include technology answers based on Formula 9-1 along with “Table” answers based on Table A-3 with df equal to the smaller of\({n_1} - 1\)and\({n_2} - 1\).)

BMI We know that the mean weight of men is greater than the mean weight of women, and the mean height of men is greater than the mean height of women. A person’s body mass index (BMI) is computed by dividing weight (kg) by the square of height (m). Given below are the BMI statistics for random samples of females and males taken from Data Set 1 “Body Data” in Appendix B.

a. Use a 0.05 significance level to test the claim that females and males have the same mean BMI.

b. Construct the confidence interval that is appropriate for testing the claim in part (a).

c. Do females and males appear to have the same mean BMI?

Female BMI: n = 70, \(\bar x\) = 29.10, s = 7.39

Male BMI: n = 80, \(\bar x\) = 28.38, s = 5.37

Testing Claims About Proportions. In Exercises 7–22, test the given claim. Identify the null hypothesis, alternative hypothesis, test statistic, P-value or critical value(s), then state the conclusion about the null hypothesis, as well as the final conclusion that addresses the original claim.

Dreaming in Black and White A study was conducted to determine the proportion of people who dream in black and white instead of color. Among 306 people over the age of 55, 68 dream in black and white, and among 298 people under the age of 25, 13 dream in black and white (based on data from “Do We Dream in Color?” by Eva Murzyn, Consciousness and Cognition, Vol. 17, No. 4). We want to use a 0.01 significance level to test the claim that the proportion of people over 55 who dream in black and white is greater than the proportion of those under 25.

a. Test the claim using a hypothesis test.

b. Test the claim by constructing an appropriate confidence interval.

c. An explanation given for the results is that those over the age of 55 grew up exposed to media that was mostly displayed in black and white. Can the results from parts (a) and (b) be used to verify that explanation?

Testing Claims About Proportions. In Exercises 7–22, test the given claim. Identify the null hypothesis, alternative hypothesis, test statistic, P-value or critical value(s), then state the conclusion about the null hypothesis, as well as the final conclusion that addresses the original claim.

Are Seat Belts Effective? A simple random sample of front-seat occupants involved in car crashes is obtained. Among 2823 occupants not wearing seat belts, 31 were killed. Among 7765 occupants wearing seat belts, 16 were killed (based on data from “Who Wants Airbags?” by Meyer and Finney, Chance, Vol. 18, No. 2). We want to use a 0.05 significance level to test the claim that seat belts are effective in reducing fatalities.

a. Test the claim using a hypothesis test.

b. Test the claim by constructing an appropriate confidence interval.

c. What does the result suggest about the effectiveness of seat belts?

In Exercises 5–20, assume that the two samples are independent simple random samples selected from normally distributed populations, and do not assume that the population standard deviations are equal. (Note: Answers in Appendix D include technology answers based on Formula 9-1 along with “Table” answers based on Table A-3 with df equal to the smaller of\({n_1} - 1\)and\({n_2} - 1\).) Car and Taxi Ages When the author visited Dublin, Ireland (home of Guinness Brewery employee William Gosset, who first developed the t distribution), he recorded the ages of randomly selected passenger cars and randomly selected taxis. The ages can be found from the license plates. (There is no end to the fun of traveling with the author.) The ages (in years) are listed below. We might expect that taxis would be newer, so test the claim that the mean age of cars is greater than the mean age of taxis.

Car

Ages

4

0

8

11

14

3

4

4

3

5

8

3

3

7

4

6

6

1

8

2

15

11

4

1

1

8

Taxi Ages

8

8

0

3

8

4

3

3

6

11

7

7

6

9

5

10

8

4

3

4

In Exercises 5–20, assume that the two samples are independent simple random samples selected from normally distributed populations, and do not assume that the population standard deviations are equal. (Note: Answers in Appendix D include technology answers based on Formula 9-1 along with “Table” answers based on Table A-3 with df equal to the smaller of n1−1 and n2−1.)Color and Cognition Researchers from the University of British Columbia conducted a study to investigate the effects of color on cognitive tasks. Words were displayed on a computer screen with background colors of red and blue. Results from scores on a test of word recall are given below. Higher scores correspond to greater word recall.

a. Use a 0.05 significance level to test the claim that the samples are from populations with the same mean.

b. Construct a confidence interval appropriate for the hypothesis test in part (a). What is it about the confidence interval that causes us to reach the same conclusion from part (a)?

c. Does the background color appear to have an effect on word recall scores? If so, which color appears to be associated with higher word memory recall scores?

Red Background n = 35, x = 15.89, s = 5.90

Blue Background n = 36, x = 12.31, s = 5.48

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