STATISITCS

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

Descriptive Statistics

• 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

ANOVA

• 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

Classification and Regression Trees

• 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)

Cluster Analysis

Hierarchical

• 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

k means

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

Crosstabulation and Measures of Association

• 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

Conjoint Analysis

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

Correlations, Distances and Similarities

• 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

Correspondence Analysis

• Simple and multiple
• QuickGraphs: vector and casewise plots

Design of Experiments

• 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

Discriminant Analysis

• Linear or quadratic functions
• Prior probabilities, contrasts
• Output: F statistics, F matrix, eigenvalues, canonical correlations, canonical scores, classification 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

Factor Analysis

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

General Linear Model (GLM)

• 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

Linear Regression

• 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

Loglinear Models

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

Missing Value Analysis

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

Mixed Regression

• 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

Multidimensional Scaling (MDS)

• 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

Nonlinear Regression

• 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

Path Analysis (RAMONA)

• 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)

Partially Ordered Sets (POSAC)

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

Perceptual Mapping

• MDPREF
• Preference mapping (vector, circle, ellipse)
• Procrustes and canonical 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

Probit

• Dummy variables and interactions

Set and Canonical Correlations

• 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

Signal Detection Analysis

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

Spatial Statistics

• 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

Survival Analysis

• 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

t-tests for Means

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

Test Item Analysis

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

Time Series

• 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

Two Stage Least Squares

• Heteroscedasticity-consistent standard errors

• Pentium / clone or above
• Microsoft® Windows® 95/98/NT 4/2000
• 32 MB RAM (minimum)
• 30MB hard disk space
• SVGA monitor