BrownMath.com → TI-83/84/89 → Box-Whisker TI-89
Updated 7 Nov 2020 (What’s New?)

Box-Whisker Plots on TI-89

Copyright © 2015–2023 by Stan Brown, BrownMath.com

Summary: You can use your TI-89 to create a box-whisker diagram, also known as a boxplot. Boxplots give you a general idea of the shape of the data, particularly its skew, and they highlight outliers in the data set.

Alternatives: If you have a TI-83/84, see Box-Whisker Plots on TI-83/84 or use MATH200A Program part 2.

Let’s make a boxplot of this data set:

11151412 9875 611
1010.5 1211132 6413.522

Step 1: Enter the numbers in a list.

Get into the Stats/List Editor. [] [APPS], select Stats/List Editor, and you should be on the list entry screen.
Enter the data points. data points entered in list1 Cursor to the heading list1 (not the first data line) and press [CLEAR] [ENTER] to clear the list.
 
Enter the x values. (The order doesn’t matter.)

Step 2: Clear other plots.

Disable any other plots and graphs that could overlay your box-whisker plot [F2] [3] turns off statistics plots, and [F2] [4] turns off graphs of equations.

Step 3: Set up the boxplot.

Get to the Plot Setup screen, and select a modified boxplot. (“Modified” means it shows outliers if there are any.) selecting modified boxplot Press [F2] [1]. Then, cursor to an empty plot, or one you don’t care about keeping.
 
Press [F1] [] [5].
Fill in the Define Plot screen. Define Plot screen; see text Use the [ALPHA] key to type list1: [ALPHA 4 makes l] [ALPHA 9 makes i] [ALPHA 3 makes s], then plain [T] [1] [ENTER] [ENTER].

Step 4: Display the boxplot.

On the box-whisker diagram, any outliers show as isolated squares. The whiskers are mix and max (disregarding any outliers), and the box is first quartile, median, and third quartile. boxplot with outliers Press [F5], which is ZoomData or “zoom to statistics data”.
Identify the outliers, if any. trace showing numerical value of outlier Press [F3] to trace on the plot. Use [] and [] to display the numbers in the five-number summary as well as any outliers. Here, you see that there is an outlier with a value of 22.

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