**Hierarchical Cluster Analysis:** *Distance - Euclidean, Maximum, Manhattan, Canberra, Binary, Minkowski. Method - ward.D, ward.D2, Single, Complete, Average, Mcquitty, Median, Centroid.*
**K-Means Cluster Analysis:** *Hartigan-Wong, Lloyd, Forgy. MacQueen.*
**Non Parametric Tests:** *Kruskal-Wallis, Wilcoxon.*
**Binomial Logistic Regression:*** Stepwise, ANOVA, Confidence Interval, Odds Ratio, covariance matrix, correlation matrix, Variable importance, Pseudo R square, Hosmer Lemeshow Goodness of fit, Likelihood Ratio Test, Wald Test, Classification Table , Classification Rate, ROC Curve.*
**Multinomial Logistic Regression****:** *Stepwise, ANOVA, Confidence Interval, Odds Ratio, Correlation Matrix, Variable Importance, Classification Table, Likelihood Ratio Test, Pseudo R*^{2}, Pearson chi-Square.
**Factor Analysis:** *Eigenvalues, Correlations of factor score estimates, Weights, Rotation Matrix, path diagram, Scree Plot, parallel Analysis plot, Correlation plot.*
**Decision Tree:**

CART: Prior probabilities, Loss matrix, Split – Information / Gini, Minimum split, Minimum bucket, Complexity parameter, Maximum depth, Cross validation, Plot, Confusion matrix
**Time Series:** *
**Neural Network: ***Normalization Method - Entropy, Softmax, Censored, Confusion Matrix.*

**STATCRAFT is currently in development and Source of the above features may get omitted or changed in the final product.*