https://file.aiquickdraw.com/mathbot/file/1726737397670iswg3zgp.jpg

To find the Interquartile Range (IQR) from the boxplot shown in the image, follow these steps:

1. **Identify Q1 (the first quartile)**: This is the left boundary of the box in the plot, which represents the 25th percentile of the data. From the plot, Q1 appears to be at 7 branches.

2. **Identify Q3 (the third quartile)**: This is the right boundary of the box, which represents the 75th percentile of the data. From the plot, Q3 appears to be at 12 branches.

3. **Calculate the IQR**: The IQR is the difference between Q3 and Q1.

\[
IQR = Q3 - Q1 = 12 - 7 = 5 \text{ branches}
\]

Therefore, the IQR is **5 branches**, corresponding to option **A**.

Do you have any questions or need more details?

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Here are 5 related questions you might explore:
1. What is the purpose of the interquartile range in data analysis?
2. How does the IQR help detect outliers in a dataset?
3. What does the whisker length in a boxplot represent?
4. How do you calculate the median from a boxplot?
5. What are other measures of spread besides the IQR?

**Tip**: The IQR is a robust measure of variability as it is not affected by extreme values or outliers in the dataset.

Learn how to find the Interquartile Range (IQR) from a boxplot. In this example, we calculate the IQR by subtracting Q1 from Q3, with data points ranging from 4 to 18 branches on 10-year-old trees. Suitable for students in Grades 7-10.

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