Statistics : methods and applications : a comprehensive reference for science, industry, and data mining

Elementary concepts in statistics — Basic statistics and tables — ANOVA/MANOVA — Association rules — Boosting trees — Canonical analysis — CHAID analysis — Classification and regression trees (CART) — Classification trees — Cluster analysis — Correspondence analysis — Data mining techniques — Discriminant function analysis — Distribution fitting — Experimental design (Industrial DOE) — Factor analysis and principal components — General discrimination analysis (GDA) — General linear models (GLM) — General regression models (GRM) — Generalized additive models (GAM) — Generalized linear/nonlinear models (GLZ) — Log linear analysis of frequency tables — Machine learning — Multivariate adaptive regression splines (MARSplines) — Multidimensional scaling (MDS) — Multiple linear regression — Neural networks — Nonlinear estimation — Nonparametric statistics — Partial least squares (PLS) — Power analysis — Process analysis — Quality control charts — Reliabilty/item analysis — Structural equation modeling — Survival/failure time analysis — Text mining — Time series/forecasting — Variance components and mixed model ANOVA/ANCOVA.