uppose you want to test the claim that u, <42. Two samples are randomly selected from each population. If a hypothesis test is performed, how should you interpret a decision that ails to reject the null hypothesis? 2A. There is not sufficient evidence to reject the claim u, <, O B. There is not sufficient evidence to support the claim u,

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Title: Hypothesis Testing: Interpreting the Failure to Reject the Null Hypothesis

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**Scenario:**

Suppose you want to test the claim that \( \mu_1 < \mu_2 \). Two samples are randomly selected from each population. If a hypothesis test is performed, how should you interpret a decision that fails to reject the null hypothesis?

**Options:**

- **A.** There is not sufficient evidence to reject the claim \( \mu_1 < \mu_2 \).

- **B.** There is not sufficient evidence to support the claim \( \mu_1 < \mu_2 \).

- **C.** There is sufficient evidence to reject the claim \( \mu_1 < \mu_2 \).

- **D.** There is sufficient evidence to support the claim \( \mu_1 < \mu_2 \).

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**Explanation:**

When a hypothesis test fails to reject the null hypothesis, it suggests that there is not enough statistical evidence to support the alternative hypothesis. This situation does not prove the null hypothesis; it merely indicates insufficient evidence against it. 

**Note:** There are no graphs or diagrams in this scenario to explain.
Transcribed Image Text:Title: Hypothesis Testing: Interpreting the Failure to Reject the Null Hypothesis --- **Scenario:** Suppose you want to test the claim that \( \mu_1 < \mu_2 \). Two samples are randomly selected from each population. If a hypothesis test is performed, how should you interpret a decision that fails to reject the null hypothesis? **Options:** - **A.** There is not sufficient evidence to reject the claim \( \mu_1 < \mu_2 \). - **B.** There is not sufficient evidence to support the claim \( \mu_1 < \mu_2 \). - **C.** There is sufficient evidence to reject the claim \( \mu_1 < \mu_2 \). - **D.** There is sufficient evidence to support the claim \( \mu_1 < \mu_2 \). --- **Explanation:** When a hypothesis test fails to reject the null hypothesis, it suggests that there is not enough statistical evidence to support the alternative hypothesis. This situation does not prove the null hypothesis; it merely indicates insufficient evidence against it. **Note:** There are no graphs or diagrams in this scenario to explain.
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