You wish to test the following claim (Ha) at a significance level of a Ho: P₁ = P2 Ha: P1 P2 You obtain a sample from the first population with 120 successes and 403 failures. You obtain a sample from the second population with 39 successes and 278 failures. The test statistic is... in the critical region not in the critical region critical value = ± test statistic = = 0.005. This test statistic leads to a decision to... reject the null hypothesis O fail to reject the null hypothesis [three decimal accuracy] [three decimal accuracy] As such, the final conclusion is that... There is sufficient evidence to support that the first population proportion is not equal to the second population proportion. There is not sufficient evidence to support that the first population proportion is not equal to the second population proportion.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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**Testing Hypothesis for Population Proportions**

**Objective:**  
You wish to test the following claim (\(H_a\)) at a significance level of \(\alpha = 0.005\).

**Null and Alternative Hypotheses:**
- \(H_0: p_1 = p_2\)
- \(H_a: p_1 \neq p_2\)

**Sample Data:**
- First population: 120 successes and 403 failures.
- Second population: 39 successes and 278 failures.

**Test Details:**
- **Critical Value:** \(\pm\) [three decimal accuracy]
- **Test Statistic:** = [three decimal accuracy]

**Decision Criteria:**
- The test statistic is...
  - \( \circ \) in the critical region
  - \( \bullet \) not in the critical region

**Decision Based on Test Statistic:**
- This test statistic leads to a decision to...
  - \( \bullet \) reject the null hypothesis
  - \( \circ \) fail to reject the null hypothesis

**Conclusion:**
- As such, the final conclusion is that...
  - \( \bullet \) There is sufficient evidence to support that the first population proportion is not equal to the second population proportion.
  - \( \circ \) There is not sufficient evidence to support that the first population proportion is not equal to the second population proportion.

The analysis confirms a statistically significant difference between the population proportions at the given significance level.
Transcribed Image Text:**Testing Hypothesis for Population Proportions** **Objective:** You wish to test the following claim (\(H_a\)) at a significance level of \(\alpha = 0.005\). **Null and Alternative Hypotheses:** - \(H_0: p_1 = p_2\) - \(H_a: p_1 \neq p_2\) **Sample Data:** - First population: 120 successes and 403 failures. - Second population: 39 successes and 278 failures. **Test Details:** - **Critical Value:** \(\pm\) [three decimal accuracy] - **Test Statistic:** = [three decimal accuracy] **Decision Criteria:** - The test statistic is... - \( \circ \) in the critical region - \( \bullet \) not in the critical region **Decision Based on Test Statistic:** - This test statistic leads to a decision to... - \( \bullet \) reject the null hypothesis - \( \circ \) fail to reject the null hypothesis **Conclusion:** - As such, the final conclusion is that... - \( \bullet \) There is sufficient evidence to support that the first population proportion is not equal to the second population proportion. - \( \circ \) There is not sufficient evidence to support that the first population proportion is not equal to the second population proportion. The analysis confirms a statistically significant difference between the population proportions at the given significance level.
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