How can I plot a bar out of a

data = 1x10 cell , where each value in the cell has a different dimension like 3x100, 3x40, 66x2 etc.

My goal is to get a bar plot, where I would have 10 group of bars and in every group three bars for each of the values. On the bar, I want it to be shown the median of the values, and I want to calculate the confidence interval and show it additionally. 

On this example there are not group of bars, but my point is to show you how I want the confidence intervals shown. On the site, where I found this example they offer a solution where they have this command line

e1 = errorbar(mean(data), ci95);

but I have the problem that it can't find any ci95

So, are there any other effective ways to do it, without installing or downloading additional services? 

I've found Patrick Happel's answer to not work because the figure window (and therefore the variable b) gets cleared out by subsequent calls to errorbar. Simply adding a hold on command takes care of this. To avoid confusion, here's a new answer that reproduces all of Patrick's original code, plus my small tweak: 

%% Old answer %Just to be safe, let's clear everything clear all data = cell(1,10); % Random length of the data l = randi(500, 10, 1) + 50; % Random "width" of the data, with 3 more likely w = randi(4, 10, 1); w(w==4) = 3; % random "direction" of the data d = randi(2, 10, 1); % sigma of the data (in fraction of mean) sigma = rand(10,1) / 3; % means of the data dmean = randi(150,10,1); dsigma = dmean.*sigma; for c = 1 : 10 if d(c) == 1 data{c} = randn(l(c), w(c)) .* dsigma(c) + dmean(c); else data{c} = randn(w(c), l(c)) .* dsigma(c) + dmean(c); end end %============================================ %Next thing is % On the bar, I want it to be shown the median of the values, and I % want to calculate the confidence interval and show it additionally. % %Are you really sure you want to plot the median? The median of some data %is not connected to the variance of the data, and hus no type of error %bars are required. I guess you want to show the mean. If you really want %to show the median, a box plot might be a better alternative. % %The following code computes and plots the mean in a bar plot: %============================================ means = zeros(numel(data),3); stds = zeros(numel(data),3); n = zeros(numel(data),3); for c = 1:numel(data) d = data{c}; if size(d,1) < size(d,2) d = d'; end cols = size(d,2); means(c, 1:cols) = nanmean(d); stds(c, 1:cols) = nanstd(d); n(c, 1:cols) = sum(~isnan((d))); end b = bar(means); %% New code %This ensures that b continues to reference existing data in the next for %loop, as the graphics objects can otherwise be deleted. hold on %% Continuing Patrick Happel's answer %============================================ %Now, we need to compute the length of the error bars. Typical choices are %the standard deviation of the data (already computed by the code above, %stored in stds), the standard error or the 95% confidence interval (which %is the 1.96fold of the standard error, assuming the underlying data %follows a normal distribution). %============================================ % for standard deviation use stds % for standard error ste = stds./sqrt(n); % for 95% confidence interval ci95 = 1.96 * ste; %============================================ %Last thing is to plot the error bars. Here I chose the ci95 as you asked %in your question, if you want to change that, simply change the variable %in the call to errorbar: %============================================ for c = 1:3 size(means(:, c)) size(b(c).XData) e = errorbar(b(c).XData + b(c).XOffset, means(:,c), ci95(:, c)); e.LineStyle = 'none'; end