[STAT Article] Step-by-Step Guide to Calculating and Analyzing Principal Component Analysis (PCA) by Hand
Principal Component Analysis (PCA) is a statistical technique used for dimensionality reduction while preserving as much variability in the data as possible. It transforms the original variables in a dataset into a new set of uncorrelated variables called principal components, ordered by the amount of variance they capture from the original dataset. Here’s the step of Principal Component Analysis (PCA). 1. Standardize the Data: Since PCA is affected by the scale of the variables, it often begins with standardizing the…