given a data matrix with columns with a total variance of , an analyst performs a pca via eigenvalue decomposition, with the resulting eigenvalues as . if the analyst wishes to reduce dimensionality with of variance explained, how many dimensions would the analyst be able to reduce down to? what would be the standard deviations of the data for these selected dimensions