At first, I learned that PCA is a different type of analysis than factor analysis: PCA is only used for data reduction and factor analysis is used for detecting latent variables that underlie observed variables. So, my take for that PCA is that it is a very different type of stats analysis than EFA.
When I read pieces of literature on exploratory factor analysis (e.g., https://stats.idre.ucla.edu/spss/seminars/introduction-to-factor-analysis/a-practical-introduction-to-factor-analysis/ ), they always specify that there are two types of EFA: one called "principal component analysis", and the other called "common factor analysis". The difference between the two is that the PCA used total variance that includes both common variance and unique variance for factoring, while common factor analysis only uses common variance for factoring. However, according to this, PCA is considered as a type of EFA according to these pieces of literature.
Now, here is my question: are the PCA I described in the above two paragraphs the same thing? Or are there actually two PCAs, with one being a totally different analysis from EFA, one being just a subtype of EFA?
