Drawing from Various Truncated Normal Distributions

Hello there!

I am running several simulations where I need to randomly draw from various kinds of truncated normal distributions. The PDFs of these distributions are shown in the attached file various_truncated_distributions.png. Ideally, when I draw from these distributions, the resulting data will mirror these PDFs. However, when I do this, I get a weird bimodal distribution, as shown in random_draw_test.png which shows the case where mu = 0. The code I used to create this graph is as follows:

 pd = makedist('Normal', 'mu', 0,'sigma',.1);
 t = truncate(pd,0,1);
 x = 0:.01:1;

 for i=1:10000
    random_number(i) = random(t); 
 end

 [histFreq, histXout] = hist(random_number, 70);
 figure; 
 hold on
 bar(histXout, histFreq/sum(histFreq)*100); 
 plot(x,pdf(t,x),'Color','blue','LineWidth',2); 
 legend({'Random Draw', 'PDF of Truncated Normal Dist'})
 title('Test of Random Draw')
 xlabel('Task-Associated Stimulus')
 ylabel('Percent')

Am I drawing from this distribution incorrectly, or do I fundamentally misunderstand what it is that I am attempting to do and something like the central limit theorem is skewing my results?

Sincerely, Colin

[Jeff Miller]

I cannot replicate your bimodal figure. When I run the code you posted, the histogram looks just like the half-normal density that is plotted.

I wonder if you forgot to clear your random_number array and the upper mode (around .5) was left over from a previous random sample with a different truncated distribution.