Practical Guide To Principal Component Methods ... -

: Those who need to analyze large multivariate datasets for research or business but prefer practical implementation over theoretical derivation.

: It simplifies complex statistical concepts into digestible pieces, focusing on intuitive explanations rather than advanced theory. Practical Guide To Principal Component Methods ...

: Factor Analysis of Mixed Data (FAMD) and Multiple Factor Analysis (MFA) for datasets with both continuous and categorical variables. : Those who need to analyze large multivariate

The book categorizes methods based on the types of data you are analyzing: Practical Guide To Principal Component Methods ...

The by Alboukadel Kassambara is widely considered an excellent resource for those who want to apply multivariate analysis without getting bogged down in heavy mathematical proofs. Why It Is Highly Rated

: Simple Correspondence Analysis (CA) for two variables and Multiple Correspondence Analysis (MCA) for more than two.