# Chapter 10 Solution (Practice + Homework)

- Page ID
- 6123

**1**.

two proportions

**3**.

matched or paired samples

**5**.

single mean

**7**.

independent group means, population standard deviations and/or variances unknown

**9**.

two proportions

**11**.

independent group means, population standard deviations and/or variances unknown

**13**.

independent group means, population standard deviations and/or variances unknown

**15**.

two proportions

**17**.

The random variable is the difference between the mean amounts of sugar in the two soft drinks.

**19**.

means

**21**.

two-tailed

**23**.

the difference between the mean life spans of whites and nonwhites

**25**.

This is a comparison of two population means with unknown population standard deviations.

**27**.

Check student’s solution.

**28**.

- Cannot accept the null hypothesis
- \(p\)-value < 0.05
- There is not enough evidence at the 5% level of significance to support the claim that life expectancy in the 1900s is different between whites and nonwhites.

**31**.

\(P^{\prime}_{O S 1}-P_{O S 2}^{\prime}\) = difference in the proportions of phones that had system failures within the first eight hours of operation with \(OS_1\) and \(OS_2\).

**34**.

proportions

**36**.

right-tailed

**38**.

The random variable is the difference in proportions (percents) of the populations that are of two or more races in Nevada and North Dakota.

**40**.

Our sample sizes are much greater than five each, so we use the normal for two proportions distribution for this hypothesis test.

**42**.

- Cannot accept the null hypothesis.
- \(p\)-value < alpha
- At the 5% significance level, there is sufficient evidence to conclude that the proportion (percent) of the population that is of two or more races in Nevada is statistically higher than that in North Dakota.

**44**.

The difference in mean speeds of the fastball pitches of the two pitchers

**46**.

–2.46

**47**.

At the 1% significance level, we can reject the null hypothesis. There is sufficient data to conclude that the mean speed of Rodriguez’s fastball is faster than Wesley’s.

**49**.

Subscripts: 1 = Food, 2 = No Food

\(H_{0} : \mu_{1} \leq \mu_{2}\)

\(H_{a} : \mu_{1}>\mu_{2}\)

**51**.

Subscripts: 1 = Gamma, 2 = Zeta

\(H_{0} : \mu_{1}=\mu_{2}\)

\(H_{a} : \mu_{1} \neq \mu_{2}\)

**53**.

There is sufficient evidence so we cannot accept the null hypothesis. The data support that the melting point for Alloy Zeta is different from the melting point of Alloy Gamma.

**54**.

the mean difference of the system failures

**56**.

With a \(p\)-value 0.0067, we can cannot accept the null hypothesis. There is enough evidence to support that the software patch is effective in reducing the number of system failures.

**60**.

\(H_{0} : \mu_{d} \geq 0\)

\(H_{a} : \mu_{d}<0\)

**63**.

We decline to reject the null hypothesis. There is not sufficient evidence to support that the medication is effective.

**65**.

Subscripts: 1: two-year colleges; 2: four-year colleges

- \(H_{0} : \mu_{1} \geq \mu_{2}\)
- \(H_{a} : \mu_{1}<\mu_{2}\)
- \(\overline{X}_{1}-\overline{X}_{2}\) is the difference between the mean enrollments of the two-year colleges and the four-year colleges.
- Student’s-\(t\)
- test statistic: -0.2480
- \(p\)-value: 0.4019
- Check student’s solution.

**67**.

Subscripts: 1: mechanical engineering; 2: electrical engineering

- \(H_{0} : \mu_{1} \geq \mu_{2}\)
- \(H_{a} : \mu_{1}<\mu_{2}\)
- \(\(\overline{X}_{1}-\overline{X}_{2}\)\) is the difference between the mean entry level salaries of mechanical engineers and electrical engineers.
- \(t_{108}\)
- test statistic: \(t = –0.82\)
- \(p\)-value: 0.2061
- Check student’s solution.

**69**.

- \(H_{0} : \mu_{1}=\mu_{2}\)
- \(H_{a} : \mu_{1} \neq \mu_{2}\)
- \(\overline{X}_{1}-\overline{X}_{2}\) is the difference between the mean times for completing a lap in races and in practices.
- \(t_{20.32}\)
- test statistic: –4.70
- \(p\)-value: 0.0001
- Check student’s solution.

**71**.

- \(H_{0} : \mu_{1}=\mu_{2}\)
- \(H_{a} : \mu_{1} \neq \mu_{2}\)
- is the difference between the mean times for completing a lap in races and in practices.
- \(t_{40.94}\)
- test statistic: –5.08
- \(p\)-value: zero
- Check student’s solution.

**74**.

c

**76**.

Test: two independent sample means, population standard deviations unknown. Random variable:

\[\overline{X}_{1}-\overline{X}_{2}\nonumber\]

Distribution: \(H_{0} : \mu_{1}=\mu_{2}\) \(H_{a} : \mu_{1}<\mu_{2}\). The mean age of entering prostitution in Canada is lower than the mean age in the United States.

Graph: left-tailed \(p\)-value : 0.0151

Decision: Cannot reject \(H_0\).

Conclusion: At the 1% level of significance, from the sample data, there is not sufficient evidence to conclude that the mean age of entering prostitution in Canada is lower than the mean age in the United States.

**78**.

d

**80**.

- \(H_{0} : P_{W}=P_{B}\)
- \(H_{a} : P_{W} \neq P_{B}\)
- The random variable is the difference in the proportions of white and black suicide victims, aged 15 to 24.
- normal for two proportions
- test statistic: –0.1944
- \(p\)-value: 0.8458
- Check student’s solution.

**82**.

Subscripts: 1 = Cabrillo College, 2 = Lake Tahoe College

- \(H_{0} : p_{1}=p_{2}\)
- \(H_{a} : p_{1} \neq p_{2}\)
- The random variable is the difference between the proportions of Hispanic students at Cabrillo College and Lake Tahoe College.
- normal for two proportions
- test statistic: 4.29
- \(p\)-value: 0.00002
- Check student’s solution.

**84**.

a

**85**.

Test: two independent sample proportions.

Random variable: \(p_{1}^{\prime}-p_{2}^{\prime}\)

Distribution: \(H_{0} : p_{1}=p_{2}\) \(H_{a} : p_{1} \neq p_{2}\). The proportion of eReader users is different for the 16- to 29-year-old users from that of the 30 and older users.

Graph: two-tailed

**87**.

Test: two independent sample proportions

Random variable: \(p_{1}^{\prime}-p_{2}^{\prime}\)

Distribution:\(H_{0} : p_{1}=p_{2}\) \(H_{a} : p_{1}>p_{2}\). A higher proportion of tablet owners are aged 16 to 29 years old than are 30 years old and older.

Graph: right-tailed

Conclusion: At the 1% level of significance, from the sample data, there is not sufficient evidence to conclude that a higher proportion of tablet owners are aged 16 to 29 years old than are 30 years old and older.

**89**.

Subscripts: 1: men; 2: women

- \(H_{0} : p_{1} \leq p_{2}\)
- \(H_{a} : p_{1}>p_{2}\)
- \(P_{1}^{\prime}-P_{2}^{\prime}\) is the difference between the proportions of men and women who enjoy shopping for electronic equipment.
- normal for two proportions
- test statistic: 0.22
- \(p\)-value: 0.4133
- Check student’s solution.

**91**.

- \(H_{0} : p_{1}=p_{2}\)
- \(H_{a} : p_{1} \neq p_{2}\)
- \(P_{1}^{\prime}-P_{2}^{\prime}\) is the difference between the proportions of men and women that have at least one pierced ear.
- normal for two proportions
- test statistic: –4.82
- \(p\)-value: zero
- Check student’s solution.

**92**.

- \(H_{0} : \mu_{d}=0\)
- \(H_{a} : \mu_{d}>0\)
- The random variable \(X_d\) is the mean difference in work times on days when eating breakfast and on days when not eating breakfast.
- \(t_9\)
- test statistic: 4.8963
- \(p\)-value: 0.0004
- Check student’s solution.
- Alpha: 0.05
- Decision: Cannot accept the null hypothesis.
- Reason for Decision: \(p\)-value < alpha
- Conclusion: At the 5% level of significance, there is sufficient evidence to conclude that the mean difference in work times on days when eating breakfast and on days when not eating breakfast has increased.

**94**.

Subscripts: 1 = boys, 2 = girls

- \(H_{0} : \mu_{1} \leq \mu_{2}\)
- \(H_{a} : \mu_{1}>\mu_{2}\)
- The random variable is the difference in the mean auto insurance costs for boys and girls.
- normal
- test statistic: \(z = 2.50\)
- \(p\)-value: 0.0062
- Check student’s solution.

**96**.

Subscripts: 1 = non-hybrid sedans, 2 = hybrid sedans

- \(H_{0} : \mu_{1} \geq \mu_{2}\)
- \(H_{a} : \mu_{1}<\mu_{2}\)
- The random variable is the difference in the mean miles per gallon of non-hybrid sedans and hybrid sedans.
- normal
- test statistic: 6.36
- \(p\)-value: 0
- Check student’s solution.

**98**.

- \(H_{0} : \mu_{d}=0\)
- \(H_{a} : \mu_{d}<0\)
- The random variable \(X_d\) is the average difference between husband’s and wife’s satisfaction level.
- \(t_9\)
- test statistic: \(t = –1.86\)
- \(p\)-value: 0.0479
- Check student’s solution

**99**.

\(p\)-value = 0.1494

At the 5% significance level, there is insufficient evidence to conclude that the medication lowered cholesterol levels after 12 weeks.

**103**.

Test: two matched pairs or paired samples (\(t\)-test)

Random variable: \(\overline{X}_{d}\)

Distribution: \(t_{12}\)

\(H_{0} : \mu_{d}=0\) \(H_{a} : \mu_{d}>0\)

The mean of the differences of new female breast cancer cases in the south between 2013 and 2012 is greater than zero. The estimate for new female breast cancer cases in the south is higher in 2013 than in 2012.

Graph: right-tailed

\(p\)-value: 0.0004

Decision: Cannot accept \(H_0\)

Conclusion: At the 5% level of significance, from the sample data, there is sufficient evidence to conclude that there was a higher estimate of new female breast cancer cases in 2013 than in 2012.

**105**.

Test: matched or paired samples (\(t\)-test)

Difference data: \(\{–0.9, –3.7, –3.2, –0.5, 0.6, –1.9, –0.5, 0.2, 0.6, 0.4, 1.7, –2.4, 1.8\}\)

Random Variable: \(\overline{X}_{d}\)

Distribution: \(H_{0} : \mu_{d}=0 H_{a} : \mu_{d}<0\)

The mean of the differences of the rate of underemployment in the northeastern states between 2012 and 2011 is less than zero. The underemployment rate went down from 2011 to 2012.

Graph: left-tailed.

Decision: Cannot reject \(H_0\).

Conclusion: At the 5% level of significance, from the sample data, there is not sufficient evidence to conclude that there was a decrease in the underemployment rates of the northeastern states from 2011 to 2012.

**107**.

e

**109**.

d

**111**.

f

**113**.

e

**115**.

f

**117**.

a