principal component analysis

Three Tips for Principal Component Analysis

June 14th, 2013 by

Principal Component Analysis (PCA) is a handy statistical tool to always have available in your data analysis tool belt.

It’s a data reduction technique, which means it’s a way of capturing the variance in many variables in a smaller, easier-to-work-with set of variables.

There are many, many details involved, though, so here are a few things to remember as you run your PCA.

1. The goal of PCA is to summarize the correlations among a set of observed variables with a smaller set of linear (more…)