I found the answer:
The following worked for me. It seems like you just want a histogram for each of the 30 cases. If so, this is done very simply using histc and bar3 (essentially just two lines of code; three if you don't use the default edges):
rng(0);
% make dummy data
ncases = 30;
N = 1000;
data = NaN(ncases, N);
for k = 1:ncases
% generate a dummy random-normal distribution
% with random mean and random standard deviation
data(k, :) = rand(1) + rand(1)*randn(N, 1);
end
% generate data for histograms: 1 histogram per column
edges = [-5:0.5:5]; % bin edges
counts = histc(data, edges, 2); % specify dim 2 to act column-wise
% plot results
hf = figure;
ha = axes;
hb = bar3(edges, counts.'); % note the transpose to get the colors right
xlabel('case number')
ylabel('bins');
zlabel('count');
