The **Interquartile Range (IQR)** measures the spread of the middle 50% of a dataset, and it is calculated as:

\[
\text{IQR} = Q_3 - Q_1
\]

Where:
- \(Q_1\) is the first quartile (25th percentile),
- \(Q_3\) is the third quartile (75th percentile).

To calculate the IQR:
1. **Sort the data** from smallest to largest.
2. **Find the quartiles** \(Q_1\) and \(Q_3\).
3. Subtract \(Q_1\) from \(Q_3\).

If you provide me with a data set, I can help you calculate the IQR directly.

Would you like help with any data? If you have any questions or need further clarification, let me know!

Here are some related questions:
1. What is the significance of the IQR in data analysis?
2. How does the IQR help identify outliers in a dataset?
3. Can the IQR be used for non-numerical data?
4. How does the IQR compare to other measures of spread like the standard deviation?
5. What are \(Q_1\) and \(Q_3\), and how are they determined for large data sets?

**Tip:** The IQR is resistant to extreme values, which makes it a great measure of spread when dealing with skewed data.

Learn how to calculate the Interquartile Range (IQR), a key concept in statistics that measures the spread of the middle 50% of data. This page provides step-by-step guidance, including sorting data, finding quartiles, and calculating IQR. Suitable for high school students in Grades 9-12.

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