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 |
 |
 |
 |
 |