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Paper 16012015Nesting Multiple Box Plots and STOCKPOTS using GPL and Lattice Overlay SAS Greg Steiner MS ABSTRACT There are times when the objective is to provide a summary table and graph for several
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How to fill out nesting multiple box plots

01
Step 1: Determine the variable that you want to display on the x-axis of the box plot.
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Step 2: Collect the data for the variable and organize it into groups or categories.
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Step 3: Decide on the nesting structure for the multiple box plots. This could involve nesting by another variable or by a combination of variables.
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Step 4: Create the box plot for each group or category, following the standard steps for creating a single box plot.
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Step 5: Arrange the multiple box plots on the same axis, ensuring that they are nested according to the chosen structure.
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Step 6: Add labels and legends to the plot to provide clarity on the variables being represented and the nesting structure.
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Step 7: Analyze the patterns and differences in the multiple box plots to draw insights and make comparisons.

Who needs nesting multiple box plots?

01
Researchers and statisticians who want to visually compare distributions across multiple groups or categories.
02
Business analysts who need to analyze and compare data from different sources or segments.
03
Data scientists who want to visualize the relationship between multiple variables using box plots.
04
Educators who are teaching statistical concepts and want to demonstrate the concept of multiple box plots.
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Anyone working with data sets that have multiple factors influencing the variable of interest.
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Nesting multiple box plots refers to displaying multiple sets of box plots within each other to compare multiple groups or variables.
Researchers, data analysts, or statisticians who want to visually explore and compare multiple sets of data.
Nesting multiple box plots can be filled out using software like R, Python, or other statistical tools that support creating box plots.
The purpose of nesting multiple box plots is to visually compare the distribution of multiple groups or variables simultaneously.
The data points, quartiles, outliers, and any differences in distribution between the nested box plots.
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