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Yes, you get different results if you don't normalize. My point was, I don't see why "you have to trivially normalize your data first" is a meaningful argument
by streptomycin 14y ago
Yes, you get different results if you don't normalize. My point was, I don't see why "you have to trivially normalize your data first" is a meaningful argument against anything.
- christopheraden 14y agoBecause normalization reduces the influence of variables that have a higher variance. In raw data, if you have marathon times and heights for runners in a race, and you measure the times in minutes and the heights in inches, the influence on the principal components from the times will likely be much more. Like all problems in statistics, it ought to depend on the specific task at hand. If there is some a priori reason to use the original scale (or a different re-weighting), it ought to be used. In general, PCA on correlation matrices is much preferred for exactly the reason you mention.
- deleted 14y ago[deleted]