Practical Guide To Principal Component Methods ... 🎉 🎁

: Specifically those looking to move beyond "old-school" base R graphics to more modern, publication-ready visualizations. Practical Guide To Principal Component Methods in R

: Simple Correspondence Analysis (CA) for two variables and Multiple Correspondence Analysis (MCA) for more than two. Practical Guide To Principal Component Methods ...

: Principal Component Analysis (PCA) for quantitative variables. : Specifically those looking to move beyond "old-school"

The book categorizes methods based on the types of data you are analyzing: 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.