How to carry out a chi-squared distribution fit?

My task is to build a matlab function with 2 inputs: the table of observed data and the level of significance. This function has to compute the chi squared test and deduce which hypothesis to accept.

Now the function is able to compute the chi square but I'm finding difficulty in using the (chi2gof)

function [chi2, df] = Untitled(n)

%% degrees of freedom
r = size(n,1);
c = size(n,2);

df = (r-1)*(c-1)


% Calculate R, C, and T
R = sum(n,2);
C = sum(n);
T = sum(R);

% Calculate \chi^2
CR = (C'*R')';
S = ((n - CR/T).^2)./(CR/T);

chi2 = sum(S(:))

[h,p, stats] = chi2gof(n,'CDF','Alpha',0.05);

end

Answer 1

[Jeff Miller]

chi2gof is not the function you want here--it is for an entirely different purpose. The last few lines should be something like:

% continued from above...
chi2 = sum(S(:));

p = chi2cdf(chi2,df,'upper');

% Now check p and reject H0 if p < your alpha level (usually 0.05);
% otherwise, do not reject.
% You have already computed everything that would be in stats

[J.Cam]

Perfect! Thank you.

[Jeff Miller]

If the answer solved your problem, please accept it.