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All (of most) of Statistics

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General linear model Generalized linear model Generalized linear mixed model Generalized additive model General additive model Non-linear least squares Generalized least squares Generalized estimation equations Mixture models Homoscedasticity Heteroscedasticity Independent observation Spatial (or temporal) dependence Normality assumption REGRESSION Random effects Random effects Random effects Non-linearity Smooth non-linearity Smooth non-linearity Overdispersion Ordination Latent variable analysis Structural equation modeling Principal component analysis Factor analysis Independent component analysis Association rules Multidimensional scaling Cluster analysis Hierarchical clustering K-means Self-organizing map K-medoids UNSUPERVISED LEARNING NON-PARAMETRIC STATISTICS SUPERVISED LEARNING Classification and regression trees Linear discriminant analysis Support vector machine Multivariate adaptive regression splines Kolmogorov-Smirnov test Wilcoxon signed-rank test Mann-Whitney U-test Kruskall-Wallis' test Friedman test Brown-Forsythe test Spearman ranck correlation Lilliefors test Shapiro-Wilk test Anderson-Darling test Resampling Boostrapping Jackknifing Permutation testing Model selection Akaike information criterion Bayesian information criterion Least-angle regression Robust statistics Sampling Statistical survey Imputation Robust regression OTHER TOPICS PHILOSOPHY OF STATISTICS Frequency probability Bayesian probability Model-II regression Fixed X (predictors measured without errors) Expected value of the error is zero Predictors and errors are independent All (or most) of Statistics

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Notes

One obvious omission from the figure is visualization. This is an conscious choise. And, I'm planning on making a smallish chart of the visualization on their own.

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