Statistics : methods and applications : a comprehensive reference for science, industry, and data mining / Thomas Hill, Pawel Lewicki.

Includes bibliographical references and index.

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 discriminant 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.