Hi @Miguel
Not sure if you can try it this way to compare the R-square value. Data that follows the bell curve tends to have a high R-squared value close to 1. Data that does not follow the bell curve usually have relatively low R-squared values.
load('normal.mat');
[N1,edges1,bin1] = histcounts(normal);
x1 = 1:length(N1);
[fitobject1, gof1] = fit(x1', N1', 'gauss1')
load('abnormal.mat');
[N2,edges2,bin2] = histcounts(abnormal);
x2 = 1:length(N2);
[fitobject2, gof2] = fit(x2', N2', 'gauss1')
subplot(211)
plot(N1), grid on, title('N_{1} follows Bell curve')
subplot(212)
plot(N2), grid on, title('N_{2} does not follows Bell curve')
