If the level of employee satisfaction drops below 0.60 overall, then there is a belief that there may be a serious problem with morale in that department. There have been rumors that the Human Resources department (hr in the data file) may be having just such issues. Using a statistical package, test to determine if the mean employee satisfaction level in the Human Resources department is less than 0.60. 1. Is satisfaction level a qualitative or quantitative variable? 2. Graph the employee satisfaction level for the Human Resources department with an appropriate graph and calculate statistics appropriate for this type of data. 3. Conduct the appropriate hypothesis test using the following steps. a. Determine the null and alternative hypotheses. b. Use a significance level of a = 0.05. c. Validate the assumptions of the hypothesis test, identify the appropriate test statistic, and compute its value. Determine the P-value. d. e. Make a decision to reject or fail to reject the null hypothesis, H. f. State the conclusion in terms of the original problem. 4. Based on our conclusion from the previous step, what type of error could we have just made (Type I or Type II)? State the practical implications of this error. 5. Would it be appropriate to compare this test to a confidence interval for the mean? Why or why not?

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Chapter1: Starting With Matlab
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Here is the data

0.75

0.74

0.75

0.84

0.63

0.69

0.83

0.9

0.09

0.4

0.37

0.44

0.85

0.78

0.42

0.91

0.92

0.84

0.91

0.81

0.89

0.37

0.9

0.38

0.45

0.38

0.42

0.82

0.11

0.42

0.39

0.11

0.1

0.84

0.43

0.75

0.37

0.1

0.44

0.25

0.44

0.37

0.58

0.4

0.51

0.8

0.42

0.31

0.44

0.83

0.75

0.93

0.81

0.87

0.78

0.84

0.69

0.61

### Employee Satisfaction Analysis

#### Overview:
If the level of employee satisfaction drops below 0.60 overall, it may indicate a serious morale issue within the department. We will use a statistical package to determine if the mean employee satisfaction level in the Human Resources (HR) department is less than 0.60, based on the provided data.

### Steps to Analyze Employee Satisfaction

1. **Identify the Nature of the Variable:**
    - **Question:** Is `satisfaction_level` a qualitative or quantitative variable?
    - **Answer:** `satisfaction_level` is a quantitative variable, as it represents a measurable amount.

2. **Visual Representation:**
    - **Task:** Graph the employee satisfaction level for the Human Resources department with an appropriate graph and calculate suitable statistics.
    - **Explanation:** Depending on the data's distribution, an appropriate graph, such as a histogram or boxplot, should be used. Calculating key statistics like mean, median, and standard deviation is essential.

3. **Hypothesis Testing:**
    - **Conduct a hypothesis test** to determine if the mean satisfaction level is below 0.60:
        a. **Hypotheses Definition:**
            - Null hypothesis (\( H_0 \)): \(\mu \geq 0.60\)
            - Alternative hypothesis (\( H_a \)): \(\mu < 0.60\)
        b. **Significance Level:**
            - Use \(\alpha = 0.05\)
        c. **Validation and Test Statistic:**
            - Validate assumptions for the test (e.g., normality), identify the appropriate test statistic (e.g., z-score or t-score), and calculate it.
        d. **P-value Calculation:**
            - Determine the P-value corresponding to the test statistic.
        e. **Decision Making:**
            - Compare the P-value with \(\alpha\) to decide whether to reject \( H_0 \).
        f. **Conclusion:**
            - State the conclusion in the context of the original problem, describing if there is enough evidence to say that the mean satisfaction level is less than 0.60.

4. **Error Analysis:**
    - **Question:** Based on your conclusion from the previous step, what type of error could have been made (Type I or Type II)? State the practical implications.
    - **Explanation:** Identify whether rejecting a true null hypothesis (Type I error) or
Transcribed Image Text:### Employee Satisfaction Analysis #### Overview: If the level of employee satisfaction drops below 0.60 overall, it may indicate a serious morale issue within the department. We will use a statistical package to determine if the mean employee satisfaction level in the Human Resources (HR) department is less than 0.60, based on the provided data. ### Steps to Analyze Employee Satisfaction 1. **Identify the Nature of the Variable:** - **Question:** Is `satisfaction_level` a qualitative or quantitative variable? - **Answer:** `satisfaction_level` is a quantitative variable, as it represents a measurable amount. 2. **Visual Representation:** - **Task:** Graph the employee satisfaction level for the Human Resources department with an appropriate graph and calculate suitable statistics. - **Explanation:** Depending on the data's distribution, an appropriate graph, such as a histogram or boxplot, should be used. Calculating key statistics like mean, median, and standard deviation is essential. 3. **Hypothesis Testing:** - **Conduct a hypothesis test** to determine if the mean satisfaction level is below 0.60: a. **Hypotheses Definition:** - Null hypothesis (\( H_0 \)): \(\mu \geq 0.60\) - Alternative hypothesis (\( H_a \)): \(\mu < 0.60\) b. **Significance Level:** - Use \(\alpha = 0.05\) c. **Validation and Test Statistic:** - Validate assumptions for the test (e.g., normality), identify the appropriate test statistic (e.g., z-score or t-score), and calculate it. d. **P-value Calculation:** - Determine the P-value corresponding to the test statistic. e. **Decision Making:** - Compare the P-value with \(\alpha\) to decide whether to reject \( H_0 \). f. **Conclusion:** - State the conclusion in the context of the original problem, describing if there is enough evidence to say that the mean satisfaction level is less than 0.60. 4. **Error Analysis:** - **Question:** Based on your conclusion from the previous step, what type of error could have been made (Type I or Type II)? State the practical implications. - **Explanation:** Identify whether rejecting a true null hypothesis (Type I error) or
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