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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.15

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=0.01. Assume (σ1)^2 = (σ2)^2


Sample statistics: x̅1= 61, s1= 3.3, n1= 5 and x̅2= 55.1, s2= 1.2, n2= 7

Verified step by step guidance
1
Identify the null hypothesis \( H_0 \) and the alternative hypothesis \( H_a \) based on the claim. Since the claim is \( \mu_1 \neq \mu_2 \), set \( H_0: \mu_1 = \mu_2 \) and \( H_a: \mu_1 \neq \mu_2 \).
Since the population variances are assumed equal (\( \sigma_1^2 = \sigma_2^2 \)), use the pooled variance formula to estimate the common variance. Calculate the pooled variance \( s_p^2 \) as: \[ s_p^2 = \frac{(n_1 - 1)s_1^2 + (n_2 - 1)s_2^2}{n_1 + n_2 - 2} \]
Calculate the test statistic \( t \) using the formula for two independent samples with equal variances: \[ t = \frac{\bar{x}_1 - \bar{x}_2}{s_p \sqrt{\frac{1}{n_1} + \frac{1}{n_2}}} \] where \( s_p = \sqrt{s_p^2} \).
Determine the degrees of freedom for the test, which is \( df = n_1 + n_2 - 2 \).
Find the critical value(s) from the \( t \)-distribution table for a two-tailed test at significance level \( \alpha = 0.01 \) with \( df \) degrees of freedom. Compare the calculated \( t \)-statistic to the critical value(s) to decide whether to reject or fail to reject the null hypothesis.

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Key Concepts

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

Hypothesis Testing for Two Population Means

This involves testing whether there is a statistically significant difference between the means of two populations. The null hypothesis typically states that the means are equal (μ1 = μ2), while the alternative reflects the claim (μ1 ≠ μ2). The test uses sample data to decide whether to reject the null hypothesis at a given significance level.
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Difference in Means: Hypothesis Tests

Pooled Variance and Equal Population Variances Assumption

When the population variances are assumed equal (σ1² = σ2²), a pooled variance estimate combines the sample variances to improve the accuracy of the test statistic. This pooled variance is a weighted average of the sample variances, accounting for different sample sizes, and is used in the calculation of the t-test statistic.
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Variance & Standard Deviation of Discrete Random Variables

Level of Significance (α) and Critical Values

The level of significance, α, is the probability of rejecting the null hypothesis when it is true (Type I error). For a two-tailed test with α = 0.01, critical values define the rejection regions in the t-distribution. If the test statistic falls beyond these critical values, the null hypothesis is rejected in favor of the alternative.
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Critical Values: z Scores
Related Practice
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=0.01. Assume (σ1)^2 = (σ2)^2


Sample statistics: x̅1= 44.5, s1= 5.85, n1= 17 and x̅2= 49.1, s2= 5.25, n2= 18

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Textbook Question

In Exercises 25–28, determine whether a normal sampling distribution can be used. If it can be used, test the claim about the difference between two population proportions p1 and p2 at the level of significance α. Assume the samples are random and independent.


Claim: p1<p2; α=0.05


Sample statistics: x1 = 86, n1=900 and x2 = 107, n2 = 1200

90
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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

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


Sample 1: The weights of 45 oranges

Sample 2: The weights of 40 grapefruits


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Textbook Question

In Exercises 17 and 18, (a) identify the claim and state Ho and Ha, 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.

44
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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=0.10


Population statistics: σ1= 0.11 and σ2= 0.10


Sample statistics: x̅1 = 0.28, n1 = 41, and x̅2= 0.33, n2= 34

45
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