A random sample of 100 observations from a population with standard deviation 39 yielded a sample mean of a. Test the null hypothesis thatu = 100 against the alternative hypothesis that u > 100, using a =0.05. Interpret the results of the test. What is the value of the test statistic? (Round to two decimal places as needed.)

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### Statistical Hypothesis Testing Example

A random sample of 100 observations from a population with a standard deviation of 39 yielded a sample mean of 107. Complete parts a through c below.

**a. Test the null hypothesis that µ = 100 against the alternative hypothesis that µ > 100, using α = 0.05. Interpret the results of the test.**

#### What is the value of the test statistic?

\[ z = \square \text{ (Round to two decimal places as needed.)} \]

This example illustrates hypothesis testing using a sample mean and known population standard deviation. The null hypothesis (\(H_0\)) states that the population mean (\(µ\)) is equal to 100, while the alternative hypothesis (\(H_1\)) states that the population mean (\(µ\)) is greater than 100. 

### Step-by-Step Solution

1. **State the Hypotheses:**

   - Null Hypothesis (\(H_0\)): \(µ = 100\)
   - Alternative Hypothesis (\(H_1\)): \(µ > 100\)

2. **Find the Test Statistic:**

   The test statistic is calculated using the formula for the z-score:
   
   \[
   z = \frac{\overline{x} - µ}{\frac{σ}{\sqrt{n}}}
   \]
   
   Where:
   - \(\overline{x}\) is the sample mean (107)
   - \(µ\) is the population mean under the null hypothesis (100)
   - \(σ\) is the population standard deviation (39)
   - \(n\) is the sample size (100)

3. **Calculate the Test Statistic:**

   \[
   z = \frac{107 - 100}{\frac{39}{\sqrt{100}}}
   \]
   
   **Note:** Use this formula and given values to compute the z-score.

4. **Compare the Test Statistic to the Critical Value:**

   For a one-tailed test with \(α = 0.05\), the critical value (z-critical) is approximately 1.645.

5. **Interpret the Results:**

   If the calculated z-value is greater than the z-critical value, we reject the null hypothesis.

**Detailed Explanation:**

- **Random Sample Size (n):** 100 observations
- **Population Standard Deviation (σ
Transcribed Image Text:### Statistical Hypothesis Testing Example A random sample of 100 observations from a population with a standard deviation of 39 yielded a sample mean of 107. Complete parts a through c below. **a. Test the null hypothesis that µ = 100 against the alternative hypothesis that µ > 100, using α = 0.05. Interpret the results of the test.** #### What is the value of the test statistic? \[ z = \square \text{ (Round to two decimal places as needed.)} \] This example illustrates hypothesis testing using a sample mean and known population standard deviation. The null hypothesis (\(H_0\)) states that the population mean (\(µ\)) is equal to 100, while the alternative hypothesis (\(H_1\)) states that the population mean (\(µ\)) is greater than 100. ### Step-by-Step Solution 1. **State the Hypotheses:** - Null Hypothesis (\(H_0\)): \(µ = 100\) - Alternative Hypothesis (\(H_1\)): \(µ > 100\) 2. **Find the Test Statistic:** The test statistic is calculated using the formula for the z-score: \[ z = \frac{\overline{x} - µ}{\frac{σ}{\sqrt{n}}} \] Where: - \(\overline{x}\) is the sample mean (107) - \(µ\) is the population mean under the null hypothesis (100) - \(σ\) is the population standard deviation (39) - \(n\) is the sample size (100) 3. **Calculate the Test Statistic:** \[ z = \frac{107 - 100}{\frac{39}{\sqrt{100}}} \] **Note:** Use this formula and given values to compute the z-score. 4. **Compare the Test Statistic to the Critical Value:** For a one-tailed test with \(α = 0.05\), the critical value (z-critical) is approximately 1.645. 5. **Interpret the Results:** If the calculated z-value is greater than the z-critical value, we reject the null hypothesis. **Detailed Explanation:** - **Random Sample Size (n):** 100 observations - **Population Standard Deviation (σ
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