The image shows box plots for two classes, Class A and Class B, which represent the test scores of 20 students in each class. To determine which statement about the classes' scores is true, let's break down the information from the box plots:

Class A:

• Minimum: Approx. 20
• First Quartile (Q1): Approx. 50
• Median (Q2): Approx. 70
• Third Quartile (Q3): Approx. 90
• Maximum: Approx. 100

Class B:

• Minimum: Approx. 30
• First Quartile (Q1): Approx. 40
• Median (Q2): Approx. 60
• Third Quartile (Q3): Approx. 70
• Maximum: Approx. 80

Key observations:

1. Median comparison: Class A has a higher median score (~70) compared to Class B (~60).
2. Spread/Interquartile Range (IQR): Class A has a larger IQR (~90 - 50 = 40) than Class B (~70 - 40 = 30), meaning the middle 50% of Class A's scores are more spread out.
3. Range: Class A’s scores range from 20 to 100 (a range of 80), while Class B’s scores range from 30 to 80 (a range of 50).

Now, based on these insights, you can determine the correct statement by analyzing the relative positions of the medians, spreads, and ranges.

Would you like more details, or help with the specific statements? Here are 5 questions that relate to this information:

1. What is the significance of the median in comparing the two classes?
2. How does the interquartile range (IQR) help us understand score distribution?
3. Why is it important to consider the range of the scores?
4. How can outliers, if any, affect the interpretation of box plots?
5. What other statistical measures could be derived from the box plot?

Tip: The IQR is a useful measure of variability because it focuses on the middle 50% of the data, filtering out extreme values.