https://file.aiquickdraw.com/mathbot/file/172457159024037t9mrb4.jpg

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### Problem Summary:
A company conducts a salary survey of its employees, yielding the following results:
- **Average (Mean) Salary**: $65,000
- **Median Salary**: $58,000
- **Standard Deviation**: $12,000

### Question:
What can you conclude about the distribution of salaries at this company? Is it skewed, and if so, in which direction?

### Solution:
To determine the skewness of the salary distribution, we can compare the mean and median values:

1. **Mean vs. Median**:
   - The **mean** salary is $65,000.
   - The **median** salary is $58,000.

When the mean is higher than the median, it generally indicates that the distribution is **right-skewed** (positively skewed). This is because the mean is pulled in the direction of the tail, where the higher salaries (outliers) are.

2. **Skewness Direction**:
   - Since the mean ($65,000) is greater than the median ($58,000), the salary distribution is **right-skewed**.

### Conclusion:
The distribution of salaries at this company is **right-skewed** (positively skewed), meaning that a relatively small number of employees have significantly higher salaries compared to the rest.

Would you like further details or have any questions?

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### Related Questions:
1. How does standard deviation relate to the distribution's spread and skewness?
2. What impact would outliers have on the mean and median in this context?
3. Can you explain the difference between skewness and kurtosis in distributions?
4. How would a left-skewed distribution affect the mean and median?
5. What would the distribution look like if the mean and median were equal?

### Tip:
Understanding the relationship between the mean, median, and skewness of a distribution is crucial in interpreting data sets, especially in fields like economics and finance where income distributions are often analyzed.

Understand the distribution of salaries at a company through the analysis of mean, median, and skewness. Explore how these statistics reveal insights into income disparities.

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