10 Principal Components Analysis
Having too many variables, and too many people or things, causes thorny problems in data analysis, and the issue is not simply the availability of sufficient computing power to handle all that data. It’s extremely difficult to reach sensible conclusions—let alone communicate them—when you’re awash in hundreds of distinct variables and tens of thousands of individual observations.
So, statisticians and theorists, beginning around 1900, started searching for methods of reducing all those variables to a smaller, more manageable set. Their aim was to reduce the information ...
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