https://file.aiquickdraw.com/mathbot/file/1729405098977as8tm919.jpg

To find the Interquartile Range (IQR), we first need to extract the numerical data from the image. From the image, the given data are:

44, 38, 52, 76, 92, 70, 88, 98, 94, 68, 24

### Steps:
1. **Arrange the data in ascending order:**
   24, 38, 44, 52, 68, 70, 76, 88, 92, 94, 98

2. **Find the lower quartile (Q1):**
   The lower quartile \( Q1 \) is the median of the lower half of the data, excluding the median if the number of data points is odd. 
   
   Data for lower half: 24, 38, 44, 52, 68

   Median of this set: \( Q1 = 44 \)

3. **Find the upper quartile (Q3):**
   The upper quartile \( Q3 \) is the median of the upper half of the data.

   Data for upper half: 76, 88, 92, 94, 98

   Median of this set: \( Q3 = 92 \)

4. **Calculate the IQR:**
   \[
   IQR = Q3 - Q1 = 92 - 44 = 48
   \]

Thus, the Interquartile Range (IQR) is **48**.

Would you like any further details or have additional questions? 

Here are some related questions:
1. What does the IQR tell us about a dataset?
2. How is the IQR useful in identifying outliers?
3. Can you calculate the range of this dataset as well?
4. How would the IQR change if we added more values to this set?
5. What other measures of spread are important alongside the IQR?

**Tip:** The IQR is a great measure of variability that is resistant to outliers, unlike the range or standard deviation.

Learn how to calculate the Interquartile Range (IQR) for the dataset [24, 38, 44, 52, 68, 70, 76, 88, 92, 94, 98]. This detailed explanation covers the steps involved, including quartile calculation and understanding variability in data. Suitable for students in Grades 9-12.

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