About STATCRAFT

Features

Currently you will be able to access the following Analytical techniques in R through STATCRAFT.

 

  • Frequencies
  • Descriptives: Count, Minimum, Maximum, Range, Mean, Sum, Standard Deviation, Variance, Standard Error of Mean, Coefficient of Variation, Kurtosis, Skewness
  • Charts: Bar Plot, Scatter Plot, Bar Plot, Box Plot, Pie Chart, Histogram, Heat Map, Pyramid Plot, Dual Axes Plot, Density Plot, Correlogram, Summary Plot, Q-Q Plot
  • t-Test: One Sample t-Test, Independent Samples t-Test, Paired Samples t-Test
  • One Way ANOVA: Holm, Hochberg, Hommel, Bonferroni, BH, BY, fdr, None, Tukey's HSD Plot, Bartlett Test, ANOVA Plot, Levene’s test
  • Two-Way ANOVA: Holm, Hochberg, Hommel, Bonferroni,  BH, none, BY, fdr, Tukey’s HSD, Levene’s Test, Tukey HSD Plot, Residuals vs fitted Plot, Normal Q-Q Plot, Scale-location Plot, Cook’s distance Plot, Residual vs leverage Plot, Cook’s distance vs leverage Plot, Interaction Plot
  • Non Parametric Tests: Kruskal-Wallis, Wilcoxon.
  • Crosstab: Count, Total, Row Proportion, Column Proportion, Table Proportion, Row Sum, Column Sum, Expected, Standardized Residuals, Adjusted Standardised Residuals, Residuals, Chi-Square Proportion, Chi-Square Statistics, Chi-Square Statistics Correlation, McNemar, Fisher
  • Group Descriptives: Mean, Maximum, Minimum, Standard Deviation, Variance, Median
  • Correlation: Pearson, Spearman, Kendall, SPLOM
  • Linear Regression: Step wise: Forward, Backward, Both. Confidence Intervals, Correlation Matrix, Covariance Matrix, Durbin-Watson, VIF, Residuals vs fitted Plot, Normal Q-Q Plot, Scale Location Plot, Cook’s Distance Plot, Residuals vs Leverage Plot, Cook’s distance vs Leverage
  • 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 R2, Pearson chi-Square
  • K-Means Cluster Analysis: Hartigan-Wong, Lloyd, Forgy. MacQueen.
  • Hierarchical Cluster Analysis: Distance - Euclidean, Maximum, Manhattan, Canberra, Binary, Minkowski. Method - ward.D, ward.D2, Single, Complete, Average, Mcquitty, Median, Centroid
  • Decision Tree:  CART: Prior probabilities, Loss matrix, Split – Information / Gini, Minimum split, Minimum bucket, Complexity parameter, Maximum depth, Cross validation, Plot, Confusion matrix.
  • Neural Network:  Normalization Method - Entropy, Softmax, Censored, Confusion Matrix
  • Time Series: Simple Exponential Smoothing, Holt’s Method, Holt Winter, ARIMA, ACF Plot, PACF Plot, Time Series Plot
  • Factor Analysis:  Eigenvalues, Correlations of factor score estimates, Weights, Rotation Matrix, Path diagram, Scree Plot, Parallel Analysis Plot, Correlation Plot
  • Survival Curve: Kaplan-Meier, Fleming-Harrington, Nelson - Altschuler
  • Cox Regression: Efron, Breslow, Exact
  • Forest Plot
  • Reports: Report Tables, Group Summaries

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

* Work in Progress