# 3 Analysis

Carrying out a comprehensive Principal Component Analysis is both an art and a science. The analyst must have some degree of analytical experience as well as a reasonable familiarity with the analyzed data. A rushed PCA analysis tends to lead to confusing results, and frustating endeavors. A well applied PCA involves a certain strategy to analyze the data, enforced with common sense, and taking certain precautions.

In this chapter, we present a methodology to carry out a Principal Component Analysis that goes above and beyond what is typically discussed in other texts about PCA. We try to stay away from the narrow perspective of using PCA within with the sole purpose of working with few variables that are compatible with a statistical model. Instead, we strongly advocate for analyses that take into account as many variables as possible. This will make the analysis richer, more *holistic*, and with more coherent interpretations.