Descriptive Statistics:

• First Quartile (Q1): 222.5
• Median (Q2): 265.0
• Third Quartile (Q3): 287.5
• Interquartile Range (IQR): 65.0

Outlier Calculation:

• Lower Bound for Outliers: $Q1 - 1.5 \times \text{IQR} = 125.0$
• Upper Bound for Outliers: $Q3 + 1.5 \times \text{IQR} = 385.0$
• Outliers: 110, 110

Observations:

• The outliers in the given data set are 110 (occurs twice).

Boxplot:

The boxplot above visually shows the spread of the data, quartiles, and outliers.

Would you like more details or have any questions?

Further Questions:

1. How is the Interquartile Range (IQR) useful in identifying outliers?
2. What are some implications of having outliers in a dataset?
3. How does the presence of outliers affect the mean and median of the dataset?
4. What methods can be used to handle outliers in data analysis?
5. Can you explain the difference between a mild and an extreme outlier?

Tip: Always check the context of your data when handling outliers, as they can sometimes represent important variations rather than errors.