How to plot a normal distribution graph to fit a bar graph?

I have a bar graph which in the x-axis shows the edge centers and y-axis are N I would like to plot a normal distribution graph to fit the bar graph.Any suggestion?I know histfit but I have the N and edges only!Thanks

[Image Analyst]

So you want to fit the Normal distribution to the binned counts instead of the actual original data that you took the histogram of? Why? And why do you have only the counts and edges and not the original data? You had to have had the original data to get the counts, right?

[Rita]

Yes,I have calculated the percentage of the bins instead of counts for the yaxis.

Answer 1

[Star Strider]

It’s easy enough to create your own version of histfit if you need to. See if this does what you want:

data = 0.5*randn(1,1000) + 2;                                       % Create Data

mu = mean(data);
sd = std(data);

ndfcn = @(mu,sd,x) exp(-(x-mu).^2 ./ (2*sd^2)) /(sd*sqrt(2*pi));    % Standard Normal Distribution

[hc,edges] = histcounts(data, 25);                                  % Histogram

ctrs = edges(1:length(edges)-1) + mean(diff(edges))/2;              % Calculate Centres
ctrsx = linspace(min(ctrs), max(ctrs));                             % High-Resolution Vector
sdnd = ndfcn(mu,sd,ctrsx);                                          % Calculate Standard Normal Distribution

figure(1)
bar(ctrs, hc)                                                       % Plot Histogram
hold on
plot(ctrsx, sdnd*max(hc)/max(sdnd), '-r', 'LineWidth',2)            % Plot Scaled Standard Normal Distribution
hold off
grid

Obviously, substitute your own data for my ‘data’ vector. I created mine to test my code.

[Rita]

Thanks a lot .

[Star Strider]

My pleasure.

Answer 2

[Walter Roberson]

I suggest reading the histfit() source and extracting the relevant portions of it -- using histfit() and figuring out a range with icdf and using pdf on the range