11.8: BoxandWhisker Plots
Learning Objectives
At the end of this lesson, students will be able to:
 Make and interpret boxandwhisker plots.
 Analyze effects of outliers.
 Make boxandwhisker plots using a graphing calculator.
Vocabulary
Terms introduced in this lesson:
 first quartile, third quartile
 five number summary
 whiskers
 interquartile range (IQR)
 range
 raw data
 ordered list
 outlier, mild outlier, extreme outlier
Teaching Strategies and Tips
Use the introduction to point out that the median can be used to divide a data set into four quarters. See also Examples 1 and 2.
 After finding the quartiles, it is possible to construct the fivenumber summary and corresponding boxandwhisker plot.
 After finding the quartiles, it is possible to calculate the IQR.
Emphasize interpreting the box plot:

\begin{align*}50 \%\end{align*}
50% of the data set lies between the first and third quartiles (IQR). 
\begin{align*}75 \%\end{align*}
75% of the data set lies above the first quartile; \begin{align*}75 \%\end{align*}75% of the data set lies below the third quartile.  The range is the distance from one whisker to the other.
 Compare the relative size of the box to the length of the whiskers: short whiskers indicate clustered data; long whiskers indicate a spreadout data set.
 If one whisker is shorter than another, then the distribution is skewed.
Construct boxandwhisker plots for two data sets and compare them sidebyside. Point out that this makes drawing inferences easy. See Example 3.
Compare the range and IQR for a data set. Ask:
 For what kind of distributions should the IQR be used? the range?
Additional Example:
For the data set below, calculate the range and IQR. Which measure of dispersion do you think will give a better indication of the spread in the data?
\begin{align*}2, 5, 8, 8, 8, 9, 9, 10, 100\end{align*}
Error Troubleshooting
NONE.
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