How to Make a Box-And-Whisker Plot (Aka Box Plot)

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How to Make a Box-And-Whisker Plot (Aka Box Plot)

How to Make a Box-and-Whisker Plot (aka Box Plot)

Box Plots separate the data into four equal sets of data and visually show “clumped” data or “spread-out” data (by the size of the quartiles). Stacked Box Plots easily show differences between two sets of data. Finally, Box Plots could be argued as the easiest statistical plot to make, that is, of course, if you know what the median is and can find it.

1) Arrange data from least to greatest OR from greatest to least. 2) Find the Minimum (the smallest number). 3) Find the Maximum (the largest number). 4) Find the Median (the middle number). 5) Find the Lower Quartile (the median of the lower half of data). 6) Find the Upper Quartile (the median of the upper half of data). 7) Next above a number line, plot the 5-Number summary and draw the Box Plot.

Example: use this data: 34 45 56 67 68 75 77 78 79 80 82 88 90 94 96

5-Number Summary: Min= 34 LQ= 67 Median= 78 UQ= 88 Max= 96

34 67 78 88 96 “Unknown Title/Data”

REMEMBER: label each point on the number line that you use and include a title, either above the box plot OR below the number line.

REMEMBER: you can make “stacked” box plots by using the same number line and including more than one box plot on it. Make sure you label each box plot! This makes comparisons much more easier.

REMEMBER: the asterisk ( * ) is for outliers. Outliers are numbers/data that are statistically different from the other numbers. You’ll learn more about this in later statistics classes. The basic check to find where outliers might exist is to do the following:

NOTE: the IQR is the interquartile range, it is found by subtracting the LQ from the UQ (IQR = UQ – LQ)

1) Take the IQR * 1.5 to get a product. 2) Take that product and ADD it to the UQ to get the point where if data exists above here, it would be considered an outlier. 3) Take product of the IQR and 1.5 and SUBTRACT it from the LQ to get the point where if data exists below here, it would be considered an outlier.

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