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.)
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.)
MATLAB: An Introduction with Applications
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Author:Amos Gilat
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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](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F05cf7d90-82b1-4600-90af-c1fd169002d7%2Fdc691793-84b4-4347-ad34-ec402ea518bc%2F6eu93ui_processed.jpeg&w=3840&q=75)
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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