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    %% Compare Measures of Dispersion
% This example shows how to compute and compare measures of dispersion for
% sample data that contains one outlier.

% Copyright 2015 The MathWorks, Inc.


%%
% Generate sample data that contains one outlier value.
x = [ones(1,6),100]

%%
% Compute the interquartile range, mean absolute deviation, range, and
% standard deviation of the sample data.
stats = [iqr(x),mad(x),range(x),std(x)]

%%
% The interquartile range (|iqr|) is the difference between the 75th and
% 25th percentile of the sample data, and is robust to outliers. The range
% (|range|) is the difference between the maximum and minimum values in the
% data, and is strongly influenced by the presence of an outlier.

%%
% Both the mean absolute deviation (|mad|) and the standard deviation
% (|std|) are sensitive to outliers. However, the mean absolute deviation
% is less sensitive than the standard deviation.