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Testing Claims About Proportions. In Exercises 7鈥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, five developed 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 subjects who were treated with OxyContin and subjects who were given a placebo.

H0:p1=p2

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

H1:p1p2

03

Calculate the sample statistics

Let n1and n2be the number of subjects treated with OxyContin and the number of subjects given a placebo, respectively.

The sample size n1 is computed below:

n1=52+175=227

The sample size n2 is computed below:

n2=5+40=45

Assume that x1 and x2 are the number ofsubjects who developed nausea and were given OxyContin and placebo, respectively.

Letp^1 be the sample proportionof subjects who developed nausea and were treated with OxyContin.

p^1=x1n1=52227=0.229

q^1=1-p^1=1-0.229=0.771

Letp^2be the sample proportion ofsubjects who developed nausea and were given a placebo.

p^2=x2n2=545=0.111

q^2=1-p^2=1-0.111=0.889

The value of the pooled sample proportion is equal to:

p=x1+x2n1+n2=52+5227+45=0.210

Hence,

q=1-p=1-0.210=0.790

04

Compute the value of the test statistic

The test statistic is equal to:

z=p^1-p^2-p1-p2pqn1+pqn2=0.229-0.111-00.2100.790227+0.2100.79045=1.776

Referring to the standard normal distribution table, the critical values of z corresponding to =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 subjects who were treated with OxyContin and subjects who 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:

p^1-p^2-E<p1-p2<p^1-p^2+E

07

Calculate the margin of error

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

E=z2p^1q^1n1+p^2q^2n2=1.960.2290.771227+0.1110.88945=0.1069

08

Construct the confidence interval

b.

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

p^1-p^2-E<p1-p2<p^1-p^2+E(0.229-0.111)-0.1069<p1-p2<(0.229-0.111)+0.10690.011<p1-p2<0.225

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

This confidence interval 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

Denomination Effect Construct the confidence interval that could be used to test the claim in Exercise 1. What feature of the confidence interval leads to the same conclusion from Exercise 1?

Units of MeasureIf the values listed in Exercise 2 are changed so that they are expressed in Celsius degrees instead of Fahrenheit degrees, how are hypothesis test results affected?

In Exercises 5鈥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 鈥淭able鈥 answers based on Table A-3 with df equal to the smaller of\({n_1} - 1\)and\({n_2} - 1\).)

Are Male Professors and Female Professors Rated Differently?

a. Use a 0.05 significance level to test the claim that two samples of course evaluation scores are from populations with the same mean. Use these summary statistics: Female professors:

n = 40, \(\bar x\)= 3.79, s = 0.51; male professors: n = 53, \(\bar x\) = 4.01, s = 0.53. (Using the raw data in Data Set 17 鈥淐ourse Evaluations鈥 will yield different results.)

b. Using the summary statistics given in part (a), construct a 95% confidence interval estimate of the difference between the mean course evaluations score for female professors and male professors.

c. Example 1 used similar sample data with samples of size 12 and 15, and Example 1 led to the conclusion that there is not sufficient evidence to warrant rejection of the null hypothesis.

Do the larger samples in this exercise affect the results much?

In Exercises 5鈥16, test the given claim.

Professor Evaluation Scores Listed below are student evaluation scores of female professorsand male professors from Data Set 17 鈥淐ourse Evaluations鈥 in Appendix B. Use a 0.05 significance level to test the claim that female professors and male professors have evaluation scores with the same variation.

Female

4.4

3.4

4.8

2.9

4.4

4.9

3.5

3.7

3.4

4.8

Male

4

3.6

4.1

4.1

3.5

4.6

4

4.3

4.5

4.3

NotationListed below are body temperatures from five different\({\bf{\bar d}}\)subjects measured at 8 AM and again at 12 AM (from Data Set 3 鈥淏ody Temperatures鈥 in Appendix B). Find the values of and\({{\bf{s}}_{\bf{d}}}\). In general, what does\({{\bf{\mu }}_{\bf{d}}}\)represent?

Temperature\(\left( {^{\bf{0}}{\bf{F}}} \right)\)at 8AM

97.8

99.0

97.4

97.4

97.5

Temperature\(\left( {^{\bf{0}}{\bf{F}}} \right)\)at 12AM

98.6

99.5

97.5

97.3

97.6

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