https://file.aiquickdraw.com/mathbot/file/1726700805925x02v0grj.jpg

Here are the results based on the data from the image:

1. **Mean salary**: \$62,296 (in thousands: 62.3).
2. **Standard deviation**: \$5,204 (in thousands: 5.2).
3. **First quartile (Q1)**: \$58,400 (in thousands: 58.4).
4. **Z-score for the first quartile**: -0.749 (approximately).
5. **Z-score for the value 49**: -2.555 (indicating that 49 is significantly lower than the mean).
6. **Salary 1 standard deviation below the mean**: \$57,092.
7. **Salary 1.4 standard deviations above the mean**: \$69,581.

### Now, here are the answers to your questions:
- **First quartile z-score**: -0.749.
- **Z-score for the value 49**: -2.555.
- **Salary 1 standard deviation below the mean**: \$57,092.
- **Salary 1.4 standard deviations above the mean**: \$69,581.

Would you like more details or have any other questions?

Here are 5 follow-up questions:
1. How is the z-score used to determine whether a value is unusual?
2. Can you explain how to interpret a z-score of -2.555?
3. What does it mean for the first quartile to have a negative z-score?
4. How can standard deviation help in comparing salaries?
5. How would the calculations change if we had more data points?

**Tip**: A z-score tells you how many standard deviations a value is from the mean. If the z-score is below -2 or above +2, it's generally considered unusual.

Find the mean, standard deviation, first quartile, z-score for certain values, and salaries 1 and 1.4 standard deviations from the mean based on the given annual salary data.

Learn how to calculate the mean, standard deviation, z-score, and quartiles based on a dataset of employee salaries. This problem explains core statistical concepts, including how to find z-scores for specific values and how to interpret quartiles in data distribution.

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