| Statistics |
Systat Version |
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13.2 |
12.0 |
11.0 |
10.2 |
| Trimmed Mean – Row & Column |
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Standard Error |
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| Confidence Interval |
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| Windsorized Mean – Row & Column |
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Standard Error |
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| Confidence Interval |
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| Probability calculator |
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| Mode – Row |
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Interquartile Range |
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| Random sampling |
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Univariate discrete and continuous distributions |
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| Multivariate distributions * |
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| Design of experiments |
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| Power analysis |
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| Descriptive Statistics |
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Column |
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| Row |
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| N-tiles, P-tiles |
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| Fitting distributions |
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Crosstabulation and measures of association |
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| List layouts, list first n levels, display rows with zero counts |
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| Mode for one-way tables |
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| Correspondence analysis |
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Simple |
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| Multiple |
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| Loglinear models |
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| Nonparametric tests |
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Jonckheere-Terpstra |
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| Fligner-Wolfe |
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| Dwass-Steel-Critchlow-Fligner and Conover-Inman |
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| Kruskal-Wallis |
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| Two-sample Kolmogorov-Smirnov |
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| Sign |
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| Wilcoxon signed rank |
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| Friedman |
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| Quade |
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| One-sample Kolmogorov-Smirnov |
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| Anderson-Darling |
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| Wald-Wolfowitz runs |
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| Multinormal tests |
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| Hypothesis Testing |
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Mean |
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| Variance |
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| Correlation |
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| Proportion |
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| Bootstrap-based p-values for all tests for mean and variance |
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| One and two sample Hotelling T2 test for mean vector of multivariate data |
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| Correlations, distances and similarities |
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| Set and canonical correlations |
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| Cronbachs alpha |
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| Linear regression |
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Save standard errors, confidence intervals |
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Least squares |
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| Bayesian |
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| Ridge |
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| Best subsets |
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Find the best models given the number of predictors
Best model by R2, Adjusted R2, Mallow’s Cp, MSE, AIC, AICc and BIC |
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| Polynomial |
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Single independent variable up to order 8, Natural and orthogonal methods
Goodness-of fit-statistics (R2 and adjusted R2) and ANOVA with p-values for all models down to linear
Quick Graphs: Confidence and prediction interval plots along with estimates, and a plot of residuals versus predicted values |
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| Robust regression |
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Least Absolute Deviation (LAD) |
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| M |
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| Least Median of Squares (LMS) |
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| Least Trimmed Squares (LTS) |
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| Scale (S) |
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| Rank |
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| Logistic regression |
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Binary, multinomial, discrete choice and conditional through separate simplified interfaces and input data formats |
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| Specify the reference level for binary and multinomial response models |
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| Probit analysis |
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| Partial least squares regression |
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| Two stage least squares regression |
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| Mixed Regression |
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| Smooth and plot |
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| Nonlinear regression |
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| ANOVA |
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Options to test normality and homoscedasticity assumptions, including Levene’s test based on median |
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| MANOVA |
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| General Linear Model |
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| Mixed model analysis |
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| Discriminant analysis |
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Classical Discriminant Analysis (Linear or quadratic) |
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| Robust Discriminant Analysis (Linear or quadratic) |
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| Cluster analysis |
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Hierarchical |
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| K-means |
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| Additive trees |
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| Factor analysis |
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| Confirmatory Factor Analysis |
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Maximum likelihood, Generalized Least-Squares, and Weighted Least-Squares methods of estimation of parameters of the CFA model |
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| Goodness-of-Fit Index (GIF), Root Mean Square Residual (RMR), Parsimonious Goodness-of- Fit Index (PGFI), AIC, BIC, McDonald’s Measure of Certainty, and Non-Normal Fit Index (NNFI) to measure the degree of conformity of the postulated factor model to the data |
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| Time series |
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ARCH models: BHHH, BFGS, and Newton-Raphson implementations, forecasts for error variances using the parameter estimates, Jarque-Bera test for normality of errors, McLeod and Lagrange Multiplier tests for ARCH effect |
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| GARCH models: BHHH, BFGS, and Newton-Raphson implementations, forecasts for error variances using the parameter estimates, Jarque-Bera test for normality of errors, McLeod and Lagrange Multiplier tests for ARCH effect |
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| Time series plot |
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| ACF, PACF, CCF |
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| Transform |
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| Moving average, LOWESS, exponential, smoothing |
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| Seasonal adjustment |
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| ARIMA |
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| Trend analysis |
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| Fourier transformation |
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| Missing value analysis |
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| Quality analysis |
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Histogram |
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| Pareto chart |
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| Box-and-Whisker Plot |
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| Process capability analysis |
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| Control charts |
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| Survival analysis |
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| Response surface methods |
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| Path analysis (RAMONA) |
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| Conjoint analysis |
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| Multidimensional scaling |
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| Perceptual mapping |
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| Partially Ordered Scalogram Analysis with Coordinates (POSAC) |
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| Test item analysis |
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| Signal detection analysis |
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| Spatial statistics |
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| Classification and regression trees |
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| Monte Carlo (Add-on) |
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IID Monte Carlo * |
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Rejection sampling * |
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Adaptive Rejection Sampling (ARS) * |
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Markov Chain Monte Carlo (MCMC) algorithms * |
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Metropolis-Hastings (M-H) algorithm * |
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Gibbs sampling algorithm * |
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Monte Carlo integration * |
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| Quality analysis (Add-on) |
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Gauge R & R studies * |
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| Sigma measurements * |
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| Taguchi’s on-line SPC * |
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| Signal-to-Noise ratio analysis of Taguchi loss functions * |
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| Environment Variables – Column |
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