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