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    %% Adjust Normal Probability Plot Line Properties

%%
% Create a 50-by-2 matrix containing 50 random numbers from each of two
% different distributions: A standard normal distribution in column 1, and
% a set of Pearson random numbers with |mu| equal to 0, |sigma| equal to 1,
% skewness equal to 0.5, and kurtosis equal to 3 (a "right-skewed"
% distribution) in column 2.
rng default  % For reproducibility
x = [normrnd(0,1,[50,1]) pearsrnd(0,1,0.5,3,[50,1])];

%%
% Create a normal probability plot for both samples on the same figure.
% Return the plot line graphic handles.
figure
h = normplot(x)
legend({'Normal','Right-Skewed'},'Location','southeast')

%%
% The handles h(1) and h(2) correspond to the data points for the normal
% and skewed distributions, respectively. The handles h(3) and h(4)
% correspond to the second and third quartile line fit to the sample data.
% The handles h(5) and h(6) correspond to the extrapolated line that
% extends to the minimum and maximum of each set of sample data.

%%
% To illustrate, increase the line width of the second and third quartile
% line for the normally distributed data sample (represented by h(3)) to 2.
h(3).LineWidth = 2;
h(4).LineWidth = 2;