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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.)

Coke and Pepsi Data Set 26 “Cola Weights and Volumes” in Appendix B includes volumes of the contents of cans of regular Coke (n = 36, x = 12.19 oz, s = 0.11 oz) and volumes of the contents of cans of regular Pepsi (n = 36, x = 12.29 oz, s = 0.09 oz).

a. Use a 0.05 significance level to test the claim that cans of regular Coke and regular Pepsi have the same mean volume.

b. Construct the confidence interval appropriate for the hypothesis test in part (a).

c. What do you conclude? Does there appear to be a difference? Is there practical significance?

Short Answer

Expert verified

a. There is sufficient evidence that there is a difference between the volumes of the contents of cans of Coke and Pepsi.

b. The confidence interval for the difference between the means of sample is (-0.052 oz,0.148 oz).

c. The result is statistically significant but has no practical significance.

Step by step solution

01

Given information

The given problem is based on the data of Coke and Pepsi. This data set contains information about the volume of the contents in cans of regular Coke and regular Pepsi, summarized as follows:

\(\begin{array}{l}{{\rm{1}}^{{\rm{st}}}}\;{\rm{sample}}\;{\rm{:Regular}}\;{\rm{coke}}\\{n_1}\; = 36,\\{s_1} = 0.11\;oz\;\\{{\bar x}_1} = 12.19\;oz\end{array}\)

\(\begin{array}{l}{{\rm{2}}^{{\rm{nd}}}}\;{\rm{sample}}\;:{\rm{Regular}}\;{\rm{Pepsi}}\;\\{n_2} = 20\;\\{s_2} = 0.09\;oz\;\\{{\bar x}_2} = 12.29\;oz\end{array}\)

02

State the hypothesis

a.

The claim is states that the mean volume of a can of Coke and a can of Pepsi is the same.

\(\begin{array}{l}{H_{0\;}}:\;{\mu _1} = {\mu _2}\\{H_1}\;:\;{\mu _1} \ne \;{\mu _2}\end{array}\)

Here,\({\mu _1},{\mu _2}\)are the population mean volume contents for Coke and Pepsi, respectively.

The samples are independent with unknown and unequal population standard deviations.

03

Compute the test statistic

The formula for t-statistic is given below.

\({t_{stat}} = \frac{{\left( {{{\bar x}_1} - {{\bar x}_2}} \right) - \left( {{\mu _1} - {\mu _2}} \right)}}{{\sqrt {\frac{{s_1^2}}{{{n_1}}} + \frac{{s_2^2}}{{{n_2}}}} }};\;({\rm{here}},\;\left( {{\mu _1} - {\mu _2}} \right)\;{\rm{is}}\;{\rm{supposed}}\;{\rm{to}}\;{\rm{be}}\;0\,)\)

04

Find critical values

For t-distribution, find the degrees of freedom as follows:

\(\begin{array}{c}df = \min \left( {\left( {{n_1} - 1} \right),\left( {{n_2} - 1} \right)} \right)\\ = \min \left( {\left( {36 - 1} \right),\left( {36 - 1} \right)} \right)\\ = 35\end{array}\)

The critical values are obtained as follows:

\(\begin{array}{c}P\left( {t > {t_{\frac{\alpha }{2}}}} \right) = \frac{\alpha }{2}\\P\left( {t > {t_{\frac{{0.05}}{2}}}} \right) = \frac{{0.05}}{2}\\P\left( {t > {t_{0.025}}} \right) = 0.025\end{array}\)

Thus, the critical value obtained from the t-table for 35 degrees of freedom is 2.0301.

05

Compute test statistic

The test statistic of the means of populations is as follows:

\(\begin{array}{c}{t_{stat}} = \frac{{\left( {{{\bar x}_1} - {{\bar x}_2}} \right)}}{{\sqrt {\frac{{s_1^2}}{{{n_1}}} + \frac{{s_2^2}}{{{n_2}}}} }}\\ = \frac{{\left( {12.19 - 12.29} \right)}}{{\sqrt {\frac{{{{\left( {0.11} \right)}^2}}}{{36}} + \frac{{{{\left( {0.09} \right)}^2}}}{{36}}} }}\\ = - 4.22159\end{array}\)

The test statistic is \({t_{stat}} = - 4.22\).

06

Decision rule using the critical value

The decision criterion for this problem statement is given below.

If\(\left| {{t_{stat}}} \right|\; > \;{t_{crit}}\); Reject a null hypothesis at \(\alpha \)level of significance

If \(\left| {{t_{stat}}} \right|\; < {t_{crit}}\) ; Fail to accept null hypothesis at \(\alpha \)level of significance

In this case, \(\left| {{t_{stat}} = - 4.222} \right|\; > \;{t_{crit}} = 2.0301\).

Thus, the null hypothesis is rejected. It shows that there is not enough evidence to support the claim that the volumes of cans of Pepsi and Coke are the same.

07

Confidence interval for the difference of means of population

b.

For the 0.05 significance test, concerning a two-tailed test, the most appropriate confidence level is 95%.

The formula for the confidence interval of the means of population is given by

\(\left( {{{\bar x}_1} - {{\bar x}_2}} \right) - E < \left( {{\mu _1} - {\mu _2}} \right) < \left( {{{\bar x}_1} - {{\bar x}_2}} \right) + E\).

Here, E is the margin of error that is computed as follows:

\(\begin{array}{c}E = {t_{\frac{\alpha }{2}}} \times \sqrt {\frac{{s_1^2}}{{{n_1}}} + \frac{{s_2^2}}{{{n_2}}}} \\ = {t_{\frac{{0.05}}{2}}} \times \sqrt {\frac{{{{0.11}^2}}}{{36}} + \frac{{{{0.09}^2}}}{{36}}} \\ = 2.0301 \times 0.024\\ = 0.0481\end{array}\)

Substitute the values in the formula.

\(\begin{array}{c}{\rm{C}}{\rm{.I}} = \left( {{{\bar x}_1} - {{\bar x}_2}} \right) - E < \left( {{\mu _1} - {\mu _2}} \right) < \left( {{{\bar x}_1} - {{\bar x}_2}} \right) + E\\ = \left( {12.19 - 12.29} \right) - 0.59 < \left( {{\mu _1} - {\mu _2}} \right) < \left( {12.19 - 12.29} \right) + 0.59\\ = - 0.052 < \left( {{\mu _1} - {\mu _2}} \right) < 0.148\end{array}\)

The 95% confidence interval includes 0, which implies that there is not enough evidence that the mean of the contents for Pepsi and Coke is the same.

There is a significant difference between the volumes of the cans.

08

Conclude the results

c.

Thus, it is concluded that there is a statistical significance for the difference in mean of the contents in Pepsi and Coke.

There does not appear to be any practical significance as the difference in the sample means is 0.10 oz, which is very small.

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Most popular questions from this chapter

Using Confidence Intervals

a. Assume that we want to use a 0.05 significance level to test the claim that p1 < p2. Which is better: A hypothesis test or a confidence interval?

b. In general, when dealing with inferences for two population proportions, which two of the following are equivalent: confidence interval method; P-value method; critical value method?

c. If we want to use a 0.05 significance level to test the claim that p1 < p2, what confidence level should we use?

d. If we test the claim in part (c) using the sample data in Exercise 1, we get this confidence interval: -0.000508 < p1 - p2 < - 0.000309. What does this confidence interval suggest about the claim?

Determining Sample Size The sample size needed to estimate the difference between two population proportions to within a margin of error E with a confidence level of 1 - a can be found by using the following expression:

\({\bf{E = }}{{\bf{z}}_{\frac{{\bf{\alpha }}}{{\bf{2}}}}}\sqrt {\frac{{{{\bf{p}}_{\bf{1}}}{{\bf{q}}_{\bf{1}}}}}{{{{\bf{n}}_{\bf{1}}}}}{\bf{ + }}\frac{{{{\bf{p}}_{\bf{2}}}{{\bf{q}}_{\bf{2}}}}}{{{{\bf{n}}_{\bf{2}}}}}} \)

Replace \({{\bf{n}}_{\bf{1}}}\;{\bf{and}}\;{{\bf{n}}_{\bf{2}}}\) by n in the preceding formula (assuming that both samples have the same size) and replace each of \({{\bf{p}}_{\bf{1}}}{\bf{,}}{{\bf{q}}_{\bf{1}}}{\bf{,}}{{\bf{p}}_{\bf{2}}}\;{\bf{and}}\;{{\bf{q}}_{\bf{2}}}\)by 0.5 (because their values are not known). Solving for n results in this expression:

\({\bf{n = }}\frac{{{\bf{z}}_{\frac{{\bf{\alpha }}}{{\bf{2}}}}^{\bf{2}}}}{{{\bf{2}}{{\bf{E}}^{\bf{2}}}}}\)

Use this expression to find the size of each sample if you want to estimate the difference between the proportions of men and women who own smartphones. Assume that you want 95% confidence that your error is no more than 0.03.

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

Question:Headache Treatment In a study of treatments for very painful “cluster” headaches, 150 patients were treated with oxygen and 148 other patients were given a placebo consisting of ordinary air. Among the 150 patients in the oxygen treatment group, 116 were free from head- aches 15 minutes after treatment. Among the 148 patients given the placebo, 29 were free from headaches 15 minutes after treatment (based on data from “High-Flow Oxygen for Treatment of Cluster Headache,” by Cohen, Burns, and Goads by, Journal of the American Medical Association, Vol. 302, No. 22). We want to use a 0.01 significance level to test the claim that the oxygen treatment is effective.

a. Test the claim using a hypothesis test.

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

c. Based on the results, is the oxygen treatment effective?

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.

Lefties In a random sample of males, it was found that 23 write with their left hands and 217 do not. In a random sample of females, it was found that 65 write with their left hands and 455 do not (based on data from “The Left-Handed: Their Sinister History,” by ElaineFowler Costas, Education Resources Information Center, Paper 399519). We want to use a 0.01significance level to test the claim that the rate of left-handedness among males is less than that among females.

a. Test the claim using a hypothesis test.

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

c. Based on the results, is the rate of left-handedness among males less than the rate of left-handedness among females?

Denomination Effect In the article “The Denomination Effect” by Priya Raghubir and Joydeep Srivastava, Journal of Consumer Research, Vol. 36, researchers reported results from studies conducted to determine whether people have different spending characteristics when they have larger bills, such as a \(20 bill, instead of smaller bills, such as twenty \)1 bills. In one trial, 89 undergraduate business students from two different colleges were randomly assigned to two different groups. In the “dollar bill” group, 46 subjects were given dollar bills; the “quarter” group consisted of 43 subjects given quarters. All subjects from both groups were given a choice of keeping the money or buying gum or mints. The article includes the claim that “money in a large denomination is less likely to be spent relative to an equivalent amount in smaller denominations.” Test that claim using a 0.05 significance level with the following sample data from the study.

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