9. The mean salary for nurses nation wide is u=$62,500 with o-6,000. A sample of 36 nurses in Connecticut have a mean salary of x $60,400. At the 5 % significance level, does the data provide sufficient evidence to show that nurse's salaries in Connecticut are lower than the national average? Give an explanation for your answer.

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### Hypothesis Testing for Nurse Salaries in Connecticut

This exercise investigates whether the mean salary of nurses in Connecticut is statistically significantly lower than the national average. The given data is as follows:

- **National Mean Salary (μ)**: $62,500
- **Standard Deviation (σ)**: $6,000
- **Sample Size (n)**: 36 nurses in Connecticut
- **Sample Mean (\(\bar{x}\))**: $60,400

We will conduct a hypothesis test at the 5% significance level to determine if the mean salary for nurses in Connecticut is lower than the national mean salary.

#### 1. State the Hypotheses
- Null Hypothesis (\(H_0\)): μ = $62,500 (The mean salary for nurses in Connecticut is equal to the national average)
- Alternative Hypothesis (\(H_1\)): μ < $62,500 (The mean salary for nurses in Connecticut is lower than the national average)

#### 2. Determine the Test Statistic
Since the standard deviation of the population is known, we use the Z-test for the hypothesis.

The Z-test statistic is calculated as:

\[ Z = \frac{\bar{x} - \mu}{\frac{\sigma}{\sqrt{n}}} \]

Plugging in the values:

\[ Z = \frac{60,400 - 62,500}{\frac{6,000}{\sqrt{36}}} \]

\[ Z = \frac{-2,100}{1,000} = -2.1 \]

#### 3. Determine the Critical Value
At the 5% significance level for a one-tailed test (lower tail), the critical value of Z is -1.645.

#### 4. Make a Decision
Compare the calculated Z-value to the critical value:

- If \( Z \leq -1.645 \), reject the null hypothesis \(H_0\)
- If \( Z > -1.645 \), fail to reject the null hypothesis \(H_0\)

Since -2.1 ≤ -1.645, we reject the null hypothesis.

#### 5. Conclusion
There is sufficient evidence at the 5% significance level to conclude that the mean salary of nurses in Connecticut is lower than the national average.

This finding is important for policymakers and stakeholders in the healthcare sector, as it may indicate a need for salary adjustments to ensure competitiveness and fair
Transcribed Image Text:### Hypothesis Testing for Nurse Salaries in Connecticut This exercise investigates whether the mean salary of nurses in Connecticut is statistically significantly lower than the national average. The given data is as follows: - **National Mean Salary (μ)**: $62,500 - **Standard Deviation (σ)**: $6,000 - **Sample Size (n)**: 36 nurses in Connecticut - **Sample Mean (\(\bar{x}\))**: $60,400 We will conduct a hypothesis test at the 5% significance level to determine if the mean salary for nurses in Connecticut is lower than the national mean salary. #### 1. State the Hypotheses - Null Hypothesis (\(H_0\)): μ = $62,500 (The mean salary for nurses in Connecticut is equal to the national average) - Alternative Hypothesis (\(H_1\)): μ < $62,500 (The mean salary for nurses in Connecticut is lower than the national average) #### 2. Determine the Test Statistic Since the standard deviation of the population is known, we use the Z-test for the hypothesis. The Z-test statistic is calculated as: \[ Z = \frac{\bar{x} - \mu}{\frac{\sigma}{\sqrt{n}}} \] Plugging in the values: \[ Z = \frac{60,400 - 62,500}{\frac{6,000}{\sqrt{36}}} \] \[ Z = \frac{-2,100}{1,000} = -2.1 \] #### 3. Determine the Critical Value At the 5% significance level for a one-tailed test (lower tail), the critical value of Z is -1.645. #### 4. Make a Decision Compare the calculated Z-value to the critical value: - If \( Z \leq -1.645 \), reject the null hypothesis \(H_0\) - If \( Z > -1.645 \), fail to reject the null hypothesis \(H_0\) Since -2.1 ≤ -1.645, we reject the null hypothesis. #### 5. Conclusion There is sufficient evidence at the 5% significance level to conclude that the mean salary of nurses in Connecticut is lower than the national average. This finding is important for policymakers and stakeholders in the healthcare sector, as it may indicate a need for salary adjustments to ensure competitiveness and fair
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