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PCA - Principal Components & Variables

PCA - Principal Components & Variables In this post, I've discussed about the relationship between Principal Components (PCs) and Variables in PCA. Most of us would've found it very difficult to figure out the corresponding variables to the PCs in PCA. Let me explain it clearly in the beginning itself that, a PC in a PCA will never corresponds to a particular Variable. A PC is a combination of 2 or more variables. Then how exactly are we going to relate a PC with variable? The rest of the article might give the answer for this question. Ok, lets begin with a quick introduction to PCA. Principal Component Analysis (PCA) is a Dimensionality Reduction technique which is used to reduce the dimension of the data with minimum loss of information. With a lot of open source tools available in the market, it is very easy to implement PCA. For example, let us take R. In R after running PCA the following statistics will be obtained. Standard Deviation, Rotat...
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Structural Equation Modelling - A basic introduction.

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An Introduction to Factor Analysis

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