Code covered by the BSD License

### Highlights fromData Analysis with MATLAB for Excel Users

from Data Analysis with MATLAB for Excel Users by Michael Agostini
Materials for public seminar of the same name (slides and demos)

checkmotor(rpm, motordata)
```function result = checkmotor(rpm, motordata)
% This function is used to determine how closely the noise profile of new
% motors matched our benchmark profile.  It also determines whether
% test-to-test differences are significant.
%

% Copyright 2006-2009 The MathWorks, Inc.

% Plot new motor's noise with benchmark data
plot(rpm,[lowerbound upperbound],':r','LineWidth',1.5); hold on
plot(rpm,motordata,'.-');title('Motor Noise Compared with Benchmark')
xlabel('Motor speed (rpm)');ylabel('Noise (dBA)');ylim([67 72]);

% Determine upper and lower bounds of benchmark model
[a,b] = size(motordata);
upperdelta = repmat(upperbound,1,b) - motordata;
lowerdelta = repmat(lowerbound,1,b) - motordata;

% Determine percentage of measurements that land within 95% confidence
% bounds of motor
count = 0;
for k = 1:b
for i = 1:a
if (upperdelta(i,k) < 0) || (lowerdelta(i,k) > 0)
count = count + 1;
end
end
end
percentage = round([1 - (count/(a*b))]*100);

% Find P-value to determine whether there are test-to-test differences
ind = find(rpm >= 7700);
motorflat = motordata(ind,:);
[pval,table,stats] = anova1(motorflat,{'Test 1';'Test 2';'Test 3';'Test 4'},'off');

result = [num2str(percentage),...
'% of the measurements are within the 95% confidence range of the benchmark model.  The P-value of the hypothesis that all tests are the same is ', ...
num2str(pval)];
```