%ttesting

%ttest((round(rtClassValue(:,7,2)) == round(Yaverage(:,7))), (round(wsClassValue(:,7,2)) == round(Yaverage(:,7))))

%Better on the final ensemble

%2 sample t test right? 

%Normality test? [a b c d ] =kstest(round(rtEnsPred(:,i)) == Yaverage(:,i))

%We want to do a one tail test. We only care if the ws is better or equal

%to rt (for now) vs ws being worse than rt. Therefore null hypothesis will

%be that wsAcc >= rtAcc (> comes from the one tail and exclusion).

%Alternative hypothesis will be wsAcc < rtAcc 

%'tail', 'left' Set the alternative hypothesis to be that the population mean of x is less than the population mean of y.

%make x = wsAcc and y = rtAcc

%Accepting the null hypothesis is success (Answer = 0. p >= 0.05)

%Rejecting the null hypothesis is failure (Meaning that wsAcc < rtAcc)

%dirty code. Overwrites the data

%for i = 1: 7

%    pwsEns(i) =  isGreaterorEqualTTest(wsEnsPred(:,i), rtEnsPred(:,i), Yaverage(:,i), Yaverage(:,i));

%end

%for i = 1: 7

%    pwsSConcatEns(i) =  isGreaterorEqualTTest(wsSConcatEnsPred(:,i), rtEnsPred(:,i), YwsMulti(:,i), Yaverage(:,i));

%end

%for i = 1:7

%    for j = 1:3

%        pws(j,i) =  isGreaterorEqualTTest(wsClassValue(:,i,j), rtClassValue(:,i,j), Yaverage(:,i), Yaverage(:,i));

%    end

%end

%for i = 1:7

%    for j = 1:3

%        pwsSConcat(j,i) =  isGreaterorEqualTTest(wsSConcatClassValue(:,i,j), rtClassValue(:,i,j), YwsMulti(:,i), Yaverage(:,i));

%    end

%end

%for i = 1:7

%    for j = 1:3

%        pwsSConcat(j,i) =  isGreaterorEqualTTest(wsSConcatClassValue(:,i,j), rtClassValue(:,i,j), YwsMulti(:,i), Yaverage(:,i));

%    end

%end

for i = 1:numCategories

    pwsMultiEnsGreater(i) =  isGreaterTTest(wsMultiEnsPred(:,i), rtEnsPred(:,i), Yaverage(:,i), Yaverage(:,i)); %low p means greater greater (not less)

    pwsMultiEnsNotLess(i) = isNotLessTTest(wsMultiEnsPred(:,i), rtEnsPred(:,i), Yaverage(:,i), Yaverage(:,i)); %high P means not less than

    pwsMultiEnsEqual(i) = isSameTTest(wsMultiEnsPred(:,i), rtEnsPred(:,i), Yaverage(:,i), Yaverage(:,i)); %high p means equal

end

wsMultiEnsImprovement = wsMultiEnsSuccess - rtEnsSuccess;

[wsMultiEnsImprovement;pwsMultiEns;pwsMultiEns<0.05];

%T test notes:

%Three types of t tests

%One Sample - If we already have a known (Iron Clad) value from other experiments and

%want to know if this experiment produced a differing result. - Nope

%Paired Two Sample - if you are testing the same guys but after changing

%something. Is this us? Same photos, different processing.

%Independant Two Sample - Probably us?

%a = Yes or no. uselsess

%b = probability they are the same. Lower is better. Less that 0.05 is good

%c = Confidence Interval. 

%d = tstat, the raw T value. df Degrees of Freedom. sd - standar deviation.