The data below shows the salaries, in thousands of dollars, of employees at the same business. 193,140,137,136,118,122,104,100,97,97,97,97,8 5,86,81,80,79,78,78,78,73,71,70,70,67,64,62,59, 59

MATLAB: An Introduction with Applications
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Chapter1: Starting With Matlab
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### Employee Salary Data Overview

The data below shows the salaries, in thousands of dollars, of employees at the same business:

```
193, 140, 137, 136, 118, 122, 104, 100, 97, 97, 97, 97, 85, 86, 81, 80, 79, 78, 78, 78, 73, 71, 70, 70, 67, 64, 62, 59, 59
```

This dataset includes the annual salaries (measured in thousands of dollars) for a group of employees. Salary values range from a high of $193,000 to a low of $59,000.

The distribution of these salaries will show us the spread, central tendency, and variability within this group of employees. Analyzing this data can provide insights into the salary structure and help in understanding compensation trends within the business.
Transcribed Image Text:### Employee Salary Data Overview The data below shows the salaries, in thousands of dollars, of employees at the same business: ``` 193, 140, 137, 136, 118, 122, 104, 100, 97, 97, 97, 97, 85, 86, 81, 80, 79, 78, 78, 78, 73, 71, 70, 70, 67, 64, 62, 59, 59 ``` This dataset includes the annual salaries (measured in thousands of dollars) for a group of employees. Salary values range from a high of $193,000 to a low of $59,000. The distribution of these salaries will show us the spread, central tendency, and variability within this group of employees. Analyzing this data can provide insights into the salary structure and help in understanding compensation trends within the business.
### Understanding Data Collection Methods: Example Analysis

**Sample Survey Scenario:**

**Question 3:**
These salaries were collected by putting a survey by the entrance and asking employees if they wanted to share their salary. 

**Analysis Question:**
Could the results show the data is unreliable? If no, why not? If yes, what can be done to improve the data?

**Detailed Analysis:**

A well-designed survey is crucial for gathering reliable data. In this scenario, the method used raises questions about data reliability. 

1. **Unreliable Data:**
    - **Voluntary Response Bias:** Since participation is voluntary, those who choose to respond may not represent the entire employee population. Individuals with extreme views (highly satisfied or highly dissatisfied) are more likely to participate.
    - **Self-Reporting Bias:** Employees may not disclose their true salaries due to privacy concerns or fear of repercussions. This can result in inaccurate data.
    - **Non-Participation:** Employees who do not participate may have significantly different salaries from those who do, leading to incomplete data.

2. **Improving Data Quality:**
    - **Confidentiality:** Ensure that responses are anonymous to encourage honest reporting. 
    - **Random Sampling:** Use a random sampling method to select participants, ensuring a more representative sample of the employee population.
    - **Incentives:** Offer incentives to increase participation rates. This can lead to a more diverse range of respondents, improving the representativeness of the data.
    - **Follow-Up Surveys:** Conduct follow-up surveys to verify the accuracy of reported salaries and gather additional context.

By addressing these factors, the reliability and accuracy of salary data can be significantly improved, leading to more trustworthy research outcomes.
Transcribed Image Text:### Understanding Data Collection Methods: Example Analysis **Sample Survey Scenario:** **Question 3:** These salaries were collected by putting a survey by the entrance and asking employees if they wanted to share their salary. **Analysis Question:** Could the results show the data is unreliable? If no, why not? If yes, what can be done to improve the data? **Detailed Analysis:** A well-designed survey is crucial for gathering reliable data. In this scenario, the method used raises questions about data reliability. 1. **Unreliable Data:** - **Voluntary Response Bias:** Since participation is voluntary, those who choose to respond may not represent the entire employee population. Individuals with extreme views (highly satisfied or highly dissatisfied) are more likely to participate. - **Self-Reporting Bias:** Employees may not disclose their true salaries due to privacy concerns or fear of repercussions. This can result in inaccurate data. - **Non-Participation:** Employees who do not participate may have significantly different salaries from those who do, leading to incomplete data. 2. **Improving Data Quality:** - **Confidentiality:** Ensure that responses are anonymous to encourage honest reporting. - **Random Sampling:** Use a random sampling method to select participants, ensuring a more representative sample of the employee population. - **Incentives:** Offer incentives to increase participation rates. This can lead to a more diverse range of respondents, improving the representativeness of the data. - **Follow-Up Surveys:** Conduct follow-up surveys to verify the accuracy of reported salaries and gather additional context. By addressing these factors, the reliability and accuracy of salary data can be significantly improved, leading to more trustworthy research outcomes.
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