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As we mentioned on page \(378\), the following relationship holds between hypothesis tests and confidence intervals for one mean \(z-\)procedures: For a two-tailed hypothesis test at the significance level \(\alpha\), the null hypothesis \(H_{0}:\mu =\mu_{0}\) will be rejected in favor of the alternative hypothesis \(H_{a}:\mu \neq \mu_{0}\) if and only if \(\mu_{0}\) lies outside the \((1-\infty)\) level confidence interval for \(\mu\). In each case, illustrate the preceding relationship by obtaining the appropriate one-mean \(z-\)interval and comparing the result to the conclusion of the hypothesis test in the specified exercise.

a. Exercise \(9.84\)

b. Exercise \(9.87\)

Short Answer

Expert verified

Part a. Both conclusions are same. i.e. the conclusion for confidence interval is same as the conclusion for hypotheses test.

Part b. Both conclusions are same. i.e. the conclusion for confidence interval is same as the conclusion for hypotheses test.

Step by step solution

01

Part a. Step 1. Given information

The null hypothesis.

\(H_{0}:\mu =\mu_{0}\)

Alternative hypothesis

\(H_{0}:\mu \neq \mu_{0}\)

02

Part a. Step 2. Calculation

Calculate the confidence interval by using MINITAB.

MINITAB output:

One-Sample Z: PERIODS

From the MINITAB output, the \(95%\) confidence interval is \((18.064, 21.207\)

The population mean \((=23)\) does not lie between lower and upper limit. Therefore, the null hypothesis is rejected at \(5%\) level.

The data provided sufficient evidence to conclude that the mean lactation period of grey seals differs from \(23\) days at \(5%\) level.

Hypothesis test

Problem \(9.84E\)

The value of test statistic is \(-4.20\) and \(P-\)value is \(0\).

Here, the \(P-\)value is less than the level of significance. i.e. \(P(=0)<\alpha (=0.5)\)

The null hypothesis is rejected at \(5%\) level.

The data provided sufficient evidence to conclude that the mean lactation period of grey seals differs from \(23\) days at \(5%\) level.

Thus, both conclusions are same. i.e. the conclusion for confidence interval is same as the conclusion for hypotheses test.

03

Part b. Step 1. Calculation

Calculate the confidence interval by using MINITAB.

MINITAB output:

One-Sample Z:

From the MINITAB output, the \(95%\) confidence interval is \((16.624, 18.976)\)

The population means \((16.7)\) lies between lower and upper limit. Therefore, the null hypothesis is not rejected at \(5%\) level.

The data does not provided sufficient evidence to conclude that the mean length of imprisonment for motor-vehicle-theft offenders in Sydney differs from the national mean in Australia.

Hypothesis test

Problem \(9.87E\)

The value of test statistic is \(1.83\) and \(P-\)value is \(0.067\).

Here, the \(P-\)value is greater than the level of significance. i.e. \(P(=0.067)>\alpha (=0.05)\)

The null hypothesis is not rejected at \(5%\) level.

The data does not provided sufficient evidence to conclude that the mean length of imprisonment for motor-vehicle-theft offenders in Sydney differs from the national mean in Australia.

Thus, both conclusions are same. i.e. the conclusion for confidence interval is same as the conclusion for hypotheses test.

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Most popular questions from this chapter

As we mentioned on page 378, the following relationship holds between hypothesis test and confidence intervals for one-mean z-procedures: For a two-tailed hypothesis test at the significance level α, the null hypothesis role="math" localid="1653038937481" H0:μ=μ0will be rejected in favor of the alternative hypothesis Ha:μ≠μ0if and only if μ0lies outside the 1-α-level confidence interval for μ. In each case, illustrate the preceding relationship by obtaining the appropriate one-mean z-interval and comparing the result to the conclusion of the hypothesis test in the specified exercise.

Part (a): Exercise 9.84

Part (b): Exercise9.87

We have been provided a sample mean, sample size, and population standard deviation. In the given case, use the one-mean z-test to perform the required hypothesis test at the 5% significance level.

x¯=23,n=24,σ=4,H0:μ=22,Ha:μ≠22

Serving Time. According to the Bureau of Crime Statistics and Research of Australia, as reported on Lawlink, the mean length of imprisonment for motor-vehicle-theft offenders in Australia is 16.7months. One hundred randomly selected motor-vehicle-theft offenders in Sydney. Australia, had a mean length of imprisonment of localid="1653225892125" 17.8months. At the localid="1653225896253" 5%significance level, do the data provide sufficient evidence to conclude that the mean length of imprisonment for motor-vehicle-theft offenders in Sydney differs from the national mean in Australia? Assume that the population standard deviation of the lengths of imprisonment for motor-vehicle-theft offenders in Sydney is localid="1653225901113" 6.0months.

In each of Exercises 9.41-9.46 ,determine the critical values for a one-mean z-test. For each exercise, draw a graph that illustrates your answer

A left-tailed test withα=0.05

Refer to Exercise 9.19. Explain what each of the following would mean.

(a) Type I error.

(b) Type II error.

(c) Correct decision.

Now suppose that the results of carrying out the hypothesis test lead to the rejection of the null hypothesis. Classify that conclusion by error type or as a correct decision if in fact the mean length of imprisonment for motor-vehicle-theft offenders in Sydney.

(d) equals the national mean of 16.7 months.

(e) differs from the national mean of 16.7 months.

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