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It looks like you're working with data on the noontime temperatures from 26 world cities, and you're being asked to construct a box-and-whisker plot.

Let's start by calculating the key components needed for a box-and-whisker plot:
1. **Minimum value** (excluding any outliers).
2. **First quartile (Q1)**: The median of the lower half of the data.
3. **Median (Q2)**: The median of the entire dataset.
4. **Third quartile (Q3)**: The median of the upper half of the data.
5. **Maximum value** (excluding any outliers).

We can then check if there are any outliers, which can be identified using the interquartile range (IQR). Outliers are values that are either:
- Below \( Q1 - 1.5 \times IQR \)
- Above \( Q3 + 1.5 \times IQR \)

Let me calculate the necessary values based on the provided data. Here's the temperature data I extracted:
- 61, 85, 67, 71, 79, 65, 66, 69, 75, 87, 62, 56, 69, 70, 59, 37, 57, 50, 62, 93, 70, 71, 44, 38, 65, 85

I will now calculate the quartiles and check for outliers.Here are the key statistics from the temperature dataHere are the key statistics from the temperature 

1. **First Quartile (Q1)**: 59.5°F
2. **Median (Q2)**: 66.5°F
3. **Third Quartile (Q3)**: 71.0°F
4. **Interquartile Range (IQR)**: 11.5°F
5. **Lower Bound for Outliers**: 42.25°F
6. **Upper Bound for Outliers**: 88.25°F

From this, we find that there are **three outliers**: 37°F, 38°F, and 93°F.

- **Minimum value (excluding outliers)**: 44°F
- **Maximum value (excluding outliers)**: 85°F

The box plot should have whiskers extending from 44°F to 85°F, with a box ranging from 59.5°F to 71.0°F. Outliers (37°F, 38°F, and 93°F) should be plotted separately outside the whiskers.

Would you like more details on how to create the box plot, or any further questions?

Here are 5 questions to consider:
1. How are quartiles calculated for larger datasets?
2. What is the role of the interquartile range in identifying outliers?
3. How does a box plot visually summarize data distribution?
4. How would the plot change if more outliers were detected?
5. Why is the median used over the mean in box plots?

**Tip**: Always double-check the outlier detection method, as different situations may call for varying thresholds beyond 1.5 times the IQR.

Construct a box-and-whisker plot (sometimes called a boxplot) by adjusting the settings. Use the given tools to plot outliers, if any.

Explore how to construct a box-and-whisker plot using temperature data from 26 world cities. Learn the steps to calculate quartiles, identify outliers, and visualize the distribution of temperatures. Suitable for high school students.

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