Let's analyze each part of the question using the box-and-whisker plot provided in the image:

1. (a) Which city had more noon temperatures above 82°F?

   • Looking at the box plots, City A has data extending above 82°F, while City B does not reach that high. So, City A had more noon temperatures above 82°F.

2. (b) Which city had a larger median noon temperature?

   • The median (the line inside the box) for City A is higher than the median for City B. So, City A had a larger median noon temperature.

3. (c) Which city had noon temperatures with a larger interquartile range (IQR)?

   • The IQR is the range within the box (from the first quartile to the third quartile). The box for City B is wider than that for City A, indicating that City B has a larger IQR.

4. (d) Which city had the highest noon temperature?

   • The maximum value (the upper whisker) is higher for City A than for City B. So, City A had the highest noon temperature.

Summary of Answers:

• (a) City A had more noon temperatures above 82°F.
• (b) City A had a larger median noon temperature.
• (c) City B had a larger interquartile range (IQR).
• (d) City A had the highest noon temperature.

Would you like further details on box-and-whisker plots or have any questions about interpreting these types of plots?

Here are five questions to expand your understanding:

1. What does the interquartile range (IQR) tell us about the spread of data in each city?
2. Why is the median a better measure of central tendency in box plots compared to the mean?
3. How can box plots help in identifying outliers in the data?
4. What can the width of a box plot indicate about the variability in temperature?
5. How would you interpret a situation where one city's plot has a much longer whisker than the other?

Tip: Box-and-whisker plots are excellent for comparing distributions across different categories, as they show median, range, and variability effectively.