Principal Component Analysis
HomePrincipal Component Analysis
Principal Component Analysis
Principal component analysis is a technique for reducing the dimensions of a set of data. Unlike factor analysis, it is not designed to uncover latent traits, but simply to reduce the number of variables while retaining as much of the variance in the original data as possible.
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You're about to do some research. You've got an idea in your field and you hope to turn it into a grant or an...

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[latexpage] On Quora, someone asked about hypothesis tests for skewness and kurtosis. I wrote an answer...

This is a talk I've given at Northeast SAS Users Group (NESUG) and at SAS Global Forum (SGF)

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