SYSTAT 10 Features List

More Graphs, More Statistics, Less Effort

General Operations Statistics Graphics System Requirements

* New in SYSTAT 10!

General Operations

• Use ASCII, Excel 97™ and earlier, SAS®*, SPSS®, BMDP™, dBASE®, ODBC* and ArcView® file formats
• Temporary data sets*
• Merge data by adding columns or rows
• Save only selected cases or specified variables
• Use up to 32,000 variables, unlimited cases
• Sort or transpose data
• Label and order categories
• Manage missing values
• Rank and standardize variables
• Compute new variables: arithmetic operators, relational operators, logical operators, IF…THEN transformations, trigonometric, exponential, logarithmic, multivariate, character, date and time functions
• Density, cumulative density, inverse function, and random number generation: uniform, normal, t, f, chi-square,gamma, beta, exponential, logistic, studentized range, Weibull, binomial and Poisson
• Matrix algebra
• Use BASIC control structure to manipulate data: read, select, sort, transform, print, save, and create random samples

• Index for easy output navigation and manipulation
• Combined, formatted statistical output and graphs
• Short, medium or long statistical output
• Headers, footers, page setup and print preview
• Save output as RTF or HTML

Windows Application

• Customizable toolbars
• File path settings from single dialog
• Global options settings from toolbar
• Extensive online help system containing 6 volume set of SYSTAT manuals: Getting Started, Statistics (, Statistics II, Graphics, Data, Language Reference
• Statistics Glossary*

• Complete coverage of menu functionality
• Interactive command entry speeds analysis
• Command files automate repetitive tasks
• Command log records session history
• Create command templates with token variables
• Save charts to BMP, WMF, EMF, PCT, EPS, JPG, and CGM*

BMDP integration (requires BMDP)

• Edit and submit BMDP command files
• BMDP output to SYSTAT main window

GraphExpress™*

• Create any SYSTAT graph within SAS® using point-and click toolbar buttons
  
• Automatic dignostic plots of SAS statistical analysis including: correspondence analysis, discriminant analysis, factor, GLM and regression
  
• Embed SYSTAT commands within SAS jobs

Statistics

• Select cases using conditional IF…THEN
• Bootstrapping
• Case and frequency weighting

• Stem and leaf display
• Mean, median, sum and number of cases
• Min, max, range and variance
• Coefficient of variation, std err of mean
• Adjustable confidence intervals of mean
• Skewness, kurtosis, including standard errors

• One-way ANOVA: multiple tests, Bonferroni, Tukey-Kramer HSD, Scheffe, Fisher's LSD
• Two-way ANOVA: post hoc tests on least squares means (Bonferroni, Tukey, LSD, Scheffe)
• Repeated measures: one-way, two or more factors, three or more factors
• Designs: unbalanced, randomized block, incomplete block, fractional factorial, mixed model, nested, split plot, Latin square, crossover and change over, Hotelling's T2
• MANOVA, ANCOVA
• Means model for missing cells designs
• Automatic outlier and influential point detection
• QuickGraph: least squares means

• Loss functions: least squares, trimmed mean, LAD, phi coefficient, Gini index, Twoing
• QuickGraph: unique tree mobile including split statistics and color coded subgroup densities (box, dot, dit, jitter, stripe)

• Euclidean, percent, gamma, Pearson,R-squared, Minkowski, chi-square, phi-square
• Linkage methods: single, complete, centroid, average, median and Ward
• QuickGraphs: dendrograms, matrix and polar

• Euclidean, MWSS, gamma, Pearson,R-squared, Minkowski, chi-square, phi-square
• QuickGraphs: parallel coordinate and mean/std deviation profile plots

• Input: similarity, dissimilarity matrices
• QuickGraphs: dendograms

• One-, two-way and multiway tables
• Row and column frequencies, percents, expected values and deviates
• List layouts, order categories, define intervals, including missing intervals
• 2 x 2 tables: likelihood ratio chi square, Yates', Fisher's, odds ratio, Yule's Q
• R x R tables: McNemar's test, Cohen's kappa
• R x C tables: unordered levels, phi, Cramer's V, contingency coefficient, uncertainty coefficient, Goodman-Kruskal's lambda
• R x C ordered levels: rho, Goodman-Kruskal's gamma, Kendall's tau-b, Stuart's tau-c, Somers' D
• Others: Mantel-Haenszel test, Cochran test

• Monotonic, linear, log and power
• Stress and Tau loss functions
• QuickGraph: utility function plot

• Continuous data: Pearson correlations, Euclidean, city, Bray-Curtis, QSK
• Rank order data: Spearman, gamma, mu2, tau
• Binomial data: S2, S3, S4, S5, S6
• Missing data: pairwise, listwise deletion, EM
• Hadi outlier detection and estimation
• Probabilities: Bonferroni, Dunn-Sidak
• Tetrachoric correlations
• QuickGraph: scatterplot matrix

• Simple and multiple
• QuickGraphs: vector and casewise plots

• Choose between Classic and Advanced DOE with dynamic wizard
• Central composite designs
• Optimal Designs
• Complete and incomplete factorial designs
• Latin square designs, 3-12 levels per factor
• Box and Hunter 2-level incomplete designs
• Taguchi designs
• Plackett and Burman designs
• Box and Behnken designs
• Mixture: lattice, centroid, axial, screening

• Linear or quadratic functions
• Prior probabilities, contrasts
• Output: F statistics, F matrix, eigenvalues, canonical correlations, canonical scores, class fication matrix, Wilk's lambda, Lawley-Hotelling, Pillai and Wilk's trace, classification tables, including jackknifed, canonical variables, covariance and correlation matrix, posterior probabilities and Mahalanobis distances
• Stepwise modeling: automatic, forward, backward and interactive stepping

• Principal components, iterated principal axis, maximum likelihood
• Rotation: varimax, quartimax, equimax, orthomax, oblimin

• Any general linear model Y = XB+e
• Any general linear hypothesis ABC' = D
• Mixed categorical and continuous variables
• Stepwise model building
• Post-hoc tests
• See also linear regression and ANOVA

• Cross validation, saving residuals and diagnostics, Durbin-Watson statistic
• Multiple linear regression
• Stepwise regression: automatic, customized and interactive stepping, partial correlations
• Hypothesis testing, mixture models
• Automatic outlier and influential point detection
• QuickGraph: residuals vs. predicted values

• Binary, multinomial, discrete choice and conditional
• Quasi maximum likelihood
• Dummy variables and interactions
• Deciles of risk, quantiles and simulation
• Forward, backward, automatic and interactive stepwise regression

• Full maximum likelihood
• Pearson and likelihood ratio chi-square
• Expected values, lambda, SE lambda
• Covariance matrix, correlation matrix
• Deviates, Pearson deviates, Iikelihood deviates, Freeman Tukey deviates, log likelihood

Missing Value Analysis

• EM Algorithm
• Regression substitution
• Save estimates, correlation, covariance, SSCP matrices

• Hierarchical Linear Models (HLM)
  
• Fixed and random effects
  
• Autocorrelated error structures
  
• Nested Models (2-Level): Repeated Measures, Clustered Data
  
• Unbalanced or balanced data
  
• Quickgraph: Scatterplot matrix of empirical Bayes estimates

• Two-way scaling: Kruskal, Guttman, Young
• Three-way scaling: INDSCAL
• Nonmetric, nonmetric unfolding
• EM estimation
• Power scaling for ratio data
• QuickGraphs: MDS plot, Shepard diagram

• Gauss Newton, Quasi Newton, simplex
• Output: predicted values, residuals, asymtotic standard errors and correlations, confidence curves and regions
• Special features: Cook-Weisberg confidence intervals, Wald intervals, Marquardting
• Robust estimation: absolute, power, trim,Huber, Hampel, t, bisquare
• Maximum likelihood estimation
• Piecewise regression, kinetic models, logistic model for quantal response data
• Exact derivatives
• QuickGraph: scatterplot with fitted curve

Nonparametric tests

• Independent samples: Kruskal-Wallis, two- sample Kolmogorov-Smirnov, Mann-Whitney
• Related variables: sign test, Wilcoxon signed rank test, Friedman test
• One-sample: Kolmogorov-Smirnov, Wald-Wolfowitz runs test

• Analyze covariance or correlation matrices
• MWL (maximum Wishart likelihood)
• GLS (generalized least squares)
• OLS (ordinary least squares)
• ADFG (asymptotically distribution free estimate biased, Gramian)
• ADFU (unbiased)

• Guttman-Shye algorithm; automatic seriation
• QuickGraph: item plot

• MDPREF
• Preference mapping (vector, circle, ellipse)
• Procrustes and canoncial rotations
• QuickGraph biplots

Power Analysis*

• Determine sample size to achieve a specified power
  
• Determine power for a single sample size
  
• Determine power for a range of sample sizes
  
• Proportions, correlations, t-tests, z-tests, ANOVA (one-way, two-way), generic designs
  
• QuickGraph: power curve

• Dummy variables and interactions

• Whole, semi and bipartial set correlations
• Rao F, R-Square, Shrunk R-Square, T-Square, Shrunk T-Square, P-Square, Shrunk P-Square Within, between and inter set correlations
• Row/Column betas, standard errors, T-statistics and probabilities
• Stewart-Love canonical redundancy index
• Canonical coefficients, loadings and redundancies
• Varimax rotation

• Models: normal, Chi-square, exponential
• QuickGraph: receiver operating characteristic curve

Smooth Module*

• 126 non-parametric smoothers* including LOESS
• Windows: fixed width or nearest neighbors
• Kernels: uniform, Epanechnikov, biweight, triweight, tricube, gaussian, gauchy
• Method: median, mean, polynomial, robust, trimmed mean
• Save predicted values and residuals

• 2D & 3D variogram, Kriging and simulation
• Variogram types: semi, covariance, correlogram, general relative, pairwise relative, semi-log, semimadogram
• Semivariogram models: spherical, exponential, gaussian, power and hole effect
• Kriging types: simple, ordinary, nonstationary and drift
• QuickGraphs: variogram and contour plot

• Kaplan-Meier and actuarial life tables
• Turnbull KM estimation (EM)
• Cumulative hazards and log cum hazards
• Cox regression, parametric models: exponential, accelerated exponential, Weibull, accelerated Weibull, lognormal, logistic
• Type I, II and III censoring
• Stratification, time dependent covariates
• Forward, backward, automatic and interactive stepwise regression
• QuickGraphs: survival, quantile, reliability and hazard

• One- and two-sample and paired t-tests with Bonferroni, Dunn-Sidak adjustments
• QuickGraphs: box/normal density overlay

• Classical analysis
• One and two parameter logistic model
• QuickGraph: item plot

• Smoothing: LOWESS, moving average, running median, and exponential
• Seasonal adjustment
• Fourier and inverse Fourier transforms
• Box-Jenkins ARIMA model
• Specify autoregressive, difference and moving average parameters
• Forecast and standard errors
• Polynomially distributed lags
• QuickGraphs: series plot, autocorrelation, partial autocorrelation, cross correlation, periodogram

• Heteroscedasticity-consistent standard errors

• Overlay an unlimited number of graphs
• Automatically plot and color subgroups side-by-side or overlaid
• Page view, drawing objects and annotations
• Point and click editing for graph location, scale, axis labels, titles, colors, symbols, and more
• Save charts to BMP, CGM, EPS, JPEG, PICT and WMF
• Graph Gallery* for automatic graph creation

• QuickGraphs automatically graph results
• Dynamic Explorer: 3-D rotation, power and log transformations, confidence intervals, smoothing parameter, bars on bar chart
• Select cases with lasso across all charts and in data editor

• Plot Medians* instead of mean for Bar, Dot, Line, Profile and Pyramid graphs
• Bar: 2-D, 3-D, stacked, error bars, repeated measures, percent, polar, mirror, mosaic
• Dot: 2-D, 3-D, line connected, error bars, repeated measures, percent, polar, mirror
• Line: 2-D, 3-D, errors, rep measures, %, mirror
• Pie: 2-D, 3-D, concentric rings, offset slice
• Profile: 2-D, 3-D, stacked, rep measures,%, mirror
• Pyramid: 2-D, 3-D, rep measures, %, mirror

• Box Plot: box and whisker, notched, dot/box
• Dot/Densities: dit, symmetric dit (dot), jitter, fuzzy and stripe

• Histogram: counts, cumulative counts, control bars/widths
• Normal and Kernel densities
• Contour and mosaic plots
• Data driven or specified intervals
• Pseudo 3-D displays, mirror plots

• Repeated measures
• Smoothers (2-D/3-D): linear, quadratic, DWLS, step, nexpo, inverse, Andrews, bisquare, Huber, Kriging
• Smoother residuals and tension parameter
• Line connected, mini spanning tree,travel-ing salesman path, Voronoi tesselation, Delaunay triangles, vectors, spikes
• Size points by influence, sunflower symbols
• Spherical/Polar and triangular coordinates

• Smoothers: log, power, LOWESS, spline,mean, median, mode, midrange, trimmed mean
• Confidence interval contours: Bivariate ellipsoid, bivariate centroid CI, regression line CI, kernal density
• Display univariate densities on borders: histogram, box, box/dot, dot, dit, frequency polygon, normal, kernel, fuzzy, stripe, jitter
• High-low-close plots (2-D)
• Mirror plots (2-D)
• Geographic projections (2-D): Gnomonic, stereo, Mercator, ortho, Lambert, Robinson, sinusoidal, Miller, Peters, fish-eye

• See 2-D scatterplot options above
• 13 theoretical densities

• X bar, X, variance, sigma, range, X bar and sigma, X bar and range, NP, P, C, U, OC, ARL, multivariate T2, Pareto, MA, EWMA, CUSUM

• Present statistical data on maps
• US: states, counties, metro areas, census tracts, and related demographics
• World: continents, nations, West European provinces
• Nine geographic projections
• Import ArcView map and data files

• Multiplots*: (similar to Trellis plots) multiple plots based on grouping variable values for bar, do, line, pplot, plot, profile, pyramid and qplot graphs
• Icon plots: Chernoff faces, Fourier blobs, histograms, profiles, thermometers, weather vanes, stars, arrows
• Parallel coordinate and Andrews' Fourier
• Function plots: specify any function

• Microsoft® Windows® 95/98/NT 4/2000; Pentium/ clone or above; 32 MB RAM min.; 30MB of storage space; SVGA monitor