how do tell if its better to  standardize your data matrix first  when you do principal component analysis in R ?   
Im trying to do principal component analysis in R . There is 2 ways of doing it , I believe. 
One is doing  principal component analysis right away the other way is  standardizing the matrix first  using s = scale(m)and then apply principal component analysis.   
How  do I tell what result is better ? What values in particular should i look at . I already managed to find the eigenvalues and eigenvectors , the proportion of  variance for each eigenvector using both methods. 
how do tell if its better to  standardize your data matrix first  when you do principal component analysis in R ?   
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Im trying to do principal component analysis in R . There is 2 ways of doing it , I believe. 
One is doing  principal component analysis right away the other way is  standardizing the matrix first  using s = scale(m)and then apply principal component analysis.   
How  do I tell what result is better ? What values in particular should i look at . I already managed to find the eigenvalues and eigenvectors , the proportion of  variance for each eigenvector using both methods. 