Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 118. Chapters: Standard deviation, Variance, Data mining, Statistical assumption, Principal component analysis, Outlier, Experimental uncertainty analysis, Cluster analysis, German tank problem, Window function, Bootstrapping, Text mining, Algorithmic inference, Collocation, Cumulative frequency analysis, Data visualization, Data transformation, Independent component analysis, Covariance matrix, Forecasting, Contingency table, Text analytics, Bootstrapping populations, Clustering high-dimensional data, Exponential smoothing, Photoanalysis, Item tree analysis, Missing data, Probit, Boolean analysis, Post-hoc analysis, Power transform, Segmented regression, Standard score, K-medoids, Exploratory data analysis, 1.96, Empirical distribution function, TinkerPlots, ANOVA-simultaneous component analysis, Neighbourhood components analysis, Index of dispersion, Cluster-weighted modeling, Explained variation, Correlation clustering, Overdispersion, Multitrait-multimethod matrix, Anscombe transform, Educational data mining, Topological data analysis, 68-95-99.7 rule, Local convex hull, Univariate analysis, Counternull, Multiple correspondence analysis, Lincoln index, Visual inspection, Evolutionary data mining, Stationary subspace analysis, Grouped data, Political forecasting, Imputation, Silhouette, Inverse Mills ratio, Natural Language Toolkit, Health care analytics, Data classification, LISREL, Barnard's test, Functional data analysis, Limited dependent variable, Visual comparison, Training set, Shape of the distribution, Test set, Data reduction, Variance-stabilizing transformation, Structured data analysis, Wide and narrow data, Normal score, Proxy, Cross tabulation, Quantile normalization, Double mass analysis, Geometric data analysis, Report mining, Grand mean, Data Discovery and Query Builder, Fathom: Dynamic Data Software, Combinat...