The boxplots provided in the image illustrate the distribution of Team A's and Team B's scores. To determine which statistics are better for comparing the two teams, let’s review the key points:

• Team A's boxplot has a larger range, indicating more variability in the data.
• Team B's boxplot is more concentrated, showing less spread.

Comparison of statistics:

• Median is useful for comparing central tendencies, especially with skewed data.
• Interquartile Range (IQR) represents the spread of the middle 50% of the data, showing how much the scores are dispersed.
• Mean is sensitive to outliers, which can affect its reliability if the data is skewed.
• Standard Deviation also measures variability but can be influenced by extreme values.

Given that boxplots highlight the median and IQR as key measures of central tendency and spread (which are robust to outliers), the better statistics for this comparison are median and IQR.

Correct answer: C. Median and IQR

Would you like more details on how IQR or median are used in this context?

Here are 5 related questions to deepen your understanding:

1. What is the difference between standard deviation and IQR when analyzing spread?
2. Why might the mean be less reliable than the median when data is skewed?
3. How does the shape of the boxplot affect the choice of statistics?
4. Can IQR alone give sufficient insight into data variability?
5. What situations would call for using standard deviation over IQR?

Tip: Always look at the shape of the boxplot before deciding between mean/standard deviation or median/IQR. Boxplots highlight skewness, which affects your choice!