function [] = bootstrap2groupsMEAN_PAIRED (ctrl, exp)

% --- prepare for resampling ---

diffs = ctrl - exp;                 % compute change from ctrl condition
                                    % to exp condition
                                    
test_stat = abs(mean(diffs))        % compute test statistic

pseudo_stat_dist = zeros(1,10000);  % create vector to store pseudo test
                                    % stats generated from resampling

% --- resampling ---

for trials = 1:10000                        % resample 10,000 times        
   
    signs = sample(length(diffs), [-1 1])'; % randomly create vector of 1's
                                            % and -1's same size as diffs
    
    pseudo_diffs = signs .* diffs;          % multiply by actual diffs to 
                                            % randomize direction of diff
    
    pseudo_stat = abs(mean(pseudo_diffs));  % compute pseudo test stat from
                                            % pseudo diffs
                                            
    pseudo_stat_dist(trials) = pseudo_stat; % store pseudo test stat to 
                                            % grow null distribution
       
end

% --- end resampling ---  

bigger = count(pseudo_stat_dist > test_stat); % count pseudo test stats 
                                              % bigger than actual stat

pval = bigger / length(pseudo_stat_dist)      % divide by total number
                                              % of pseudo test stats to 
                                              % compute p-value
                                              % could use proportion()

hist(pseudo_stat_dist)                        % show histogram of pseudo
    title('Pseudo test stat distribution')    % test stats
    xlabel('Pseudo test stat')
    ylabel('Frequency')