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The question asks to **select the true statement** about the interquartile range (IQR). Let’s break down the options:

1. **"The interquartile range (IQR) is influenced by outliers."**  
   - **Incorrect**: IQR is specifically designed to reduce the influence of outliers by focusing on the middle 50% of the data.

2. **"The interquartile range (IQR) covers the middle 50% of a data set."**  
   - **Correct**: The IQR is the difference between the third quartile (Q3) and the first quartile (Q1), representing the range of the middle 50% of the data.

3. **"The interquartile range (IQR) is the average value of a data set."**  
   - **Incorrect**: The IQR is not an average or mean. It measures the spread of the middle 50% of the data.

4. **"The interquartile range (IQR) is the middle value of a data set."**  
   - **Incorrect**: The middle value of a dataset is the **median**, not the IQR.

### **Answer**:
The correct statement is:  
**"The interquartile range (IQR) covers the middle 50% of a data set."**

Would you like to explore more about IQR or how it is used in statistics?

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Here are **5 related questions** for further learning:
1. How do you calculate the IQR from a given data set?
2. Why is IQR preferred over range when dealing with skewed data?
3. What is the relationship between IQR and box plots?
4. How do outliers affect the mean and standard deviation?
5. Can two data sets have the same IQR but different ranges?

**Tip**: The IQR is a great way to detect potential outliers. Any data point outside the range \([Q1 - 1.5 \times IQR, Q3 + 1.5 \times IQR]\) is usually considered an outlier.

Select the statement that is TRUE about the interquartile range (IQR).

Learn about the interquartile range (IQR), a statistical concept that covers the middle 50% of a data set. This page explains the IQR formula, how it's calculated, and why it helps reduce the effect of outliers in statistical analysis. Suitable for students in Grades 10-12.

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