Principal component Analysis example on Matlab

I think there is something wrong here. I am applying the PCA through the statistical tool. I have a data XData that range from 1-0.9 with 512 dimension. I am using the PCA to reduce the dimension. I was following the example on: http://www.mathworks.com/help/stats/feature-transformation.html#f75476

I have applied : [coeff,score,latent] = pca(XData);

Then to transform the coefficients so they are orthonormal :

 coefforth = inv(diag(std(XData)))*wcoeff;

when I test the data using : cscores = zscore(XData)*coefforth;

I can see that cscores and score are both different. Note that I didn’t need to wight my data.

I have also tried with a new data set :