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Ch. 8 - Hypothesis Testing with Two Samples
Larson - Elementary Statistics: Picturing the World 8th Edition
Larson8th EditionElementary Statistics: Picturing the WorldISBN: 9780137493470Not the one you use?Change textbook
Chapter 8, Problem 8.RE.18b

"In Exercises 17 and 18, (b) find the critical value(s) and identify the rejection region(s), Assume the samples are random and independent, and the populations are normally distributed.


A real estate agent claims that there is no difference between the mean household incomes of two neighborhoods. The mean income of 12 randomly selected households from the first neighborhood is \$52,750 with a standard deviation of \$2900. In the second neighborhood, 10 randomly selected households have a mean income of \$51,200 with a standard deviation of \$2225. At α=0.01, can you reject the real estate agent’s claim? Assume the population variances are equal."

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Step 1: Identify the hypotheses for the test. Since the agent claims no difference in mean incomes, the null hypothesis is \(H_0: \mu_1 = \mu_2\), and the alternative hypothesis is \(H_a: \mu_1 \neq \mu_2\) (a two-tailed test).
Step 2: Determine the significance level \(\alpha = 0.01\) and the degrees of freedom for the test. Since population variances are assumed equal, use the pooled variance approach. The degrees of freedom is \(df = n_1 + n_2 - 2\), where \(n_1\) and \(n_2\) are the sample sizes.
Step 3: Find the critical value(s) from the \(t\)-distribution for a two-tailed test at \(\alpha = 0.01\) with \(df\) degrees of freedom. The critical values are \(\pm t_{\alpha/2, df}\), which define the rejection regions.
Step 4: Define the rejection regions as \(t < -t_{\alpha/2, df}\) or \(t > t_{\alpha/2, df}\). If the calculated test statistic falls into either region, reject the null hypothesis.
Step 5: (For completeness) To test the claim, calculate the pooled standard deviation, then compute the test statistic using the formula \(t = \frac{\bar{x}_1 - \bar{x}_2}{s_p \sqrt{\frac{1}{n_1} + \frac{1}{n_2}}}\), where \(s_p\) is the pooled standard deviation. Compare this \(t\) value to the critical values to decide whether to reject \(H_0\).

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Key Concepts

Here are the essential concepts you must grasp in order to answer the question correctly.

Hypothesis Testing

Hypothesis testing is a statistical method used to decide whether there is enough evidence to reject a null hypothesis. In this question, the null hypothesis states that the mean incomes of the two neighborhoods are equal. The alternative hypothesis suggests a difference exists. The test evaluates sample data to determine if observed differences are statistically significant at a given significance level (α).
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Performing Hypothesis Tests: Proportions

Two-Sample t-Test for Means with Equal Variances

This test compares the means of two independent samples assuming their population variances are equal. It uses a pooled variance estimate to calculate the test statistic, which follows a t-distribution with degrees of freedom based on sample sizes. This approach is appropriate here because the problem states equal variances and normal populations.
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Difference in Means: Hypothesis Tests

Critical Value and Rejection Region

The critical value is a threshold from the t-distribution that defines the boundary of the rejection region for the test statistic at a chosen significance level (α=0.01). If the calculated test statistic falls into this region, the null hypothesis is rejected. Identifying these values helps determine whether the observed data provide strong enough evidence against the null hypothesis.
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Critical Values: t-Distribution
Related Practice
Textbook Question

In Exercises 17 and 18, (c) find the standardized test statistic t, Assume the samples are random and independent, and the populations are normally distributed.


A real estate agent claims that there is no difference between the mean household incomes of two neighborhoods. The mean income of 12 randomly selected households from the first neighborhood is \$52,750 with a standard deviation of \$2900. In the second neighborhood, 10 randomly selected households have a mean income of \$51,200 with a standard deviation of \$2225. At α=0.01, can you reject the real estate agent’s claim? Assume the population variances are equal.

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Textbook Question

Take this test as you would take a test in class.For each exercise, perform the steps below.

c.Find the critical value(s) and identify the rejection region(s).



A real estate agency says that the mean home sales price in Olathe, Kansas, is greater than in Rolla, Missouri. The mean home sales price for 39 homes in Olathe is \$392,453. Assume the population standard deviation is \$224,902. The mean home sales price for 38 homes in Rolla is \$285,787. Assume the population standard deviation is \$330,578. At α=0.05, is there enough evidence to support the agency’s claim? (Adapted from Realtor.com)

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Textbook Question

In Exercises 1–4, classify the two samples as independent or dependent and justify your answer.


Sample 1: The fuel efficiencies of 12 cars

Sample 2: The fuel efficiencies of the same 12 cars using an alternative fuel




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Textbook Question

In Exercises 11–16, test the claim about the difference between two population means μ1 and μ2 at the level of significance α. Assume the samples are random and independent, and the populations are normally distributed.


Claim: μ1= μ2; α=0.05. Assume (σ1)^2 = (σ2)^2


Sample statistics: x̅1=228, s1=27, n1= 20 and x̅2=207, s2=25, n2= 13

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Textbook Question

In Exercises 5–8, test the claim about the difference between two population means μ1 and μ2 at the level of significance α. Assume the samples are random and independent, and the populations are normally distributed.


Claim: μ1≠μ2; α=0.05


Population statistics: σ1= 14 and σ2= 15


Sample statistics: x̅1 = 87, n1 = 410, and x̅2= 85, n2= 340

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Textbook Question

Take this test as you would take a test in class.For each exercise, perform the steps below.

a. Identify the claim and state and


A real estate agency says that the mean home sales price in Olathe, Kansas, is greater than in Rolla, Missouri. The mean home sales price for 39 homes in Olathe is \$392,453. Assume the population standard deviation is \$224,902. The mean home sales price for 38 homes in Rolla is \$285,787. Assume the population standard deviation is \$330,578. At α=0.05, is there enough evidence to support the agency’s claim? (Adapted from Realtor.com)

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