StatSoft's flagship product line is the STATISTICA suite of analytics software products. STATISTICA provides the most comprehensive array of data analysis, data management, data visualization and data mining procedures. Its techniques include the widest selection of predictive modeling, clustering, classification and exploratory techniques in one software platform.

STATISTICA analytic capabilities are complemented by the following unique features:

• Database Querying
• Data Visualization
• Automation using STATISTICA Visual Basic

Any of the products and modules listed below can be deployed within the Enterprise and Web-Based STATISTICA server products.

Products	Modules
STATISTICA Base	Descriptive statistics, breakdowns, and exploratory data analysis Correlations Basic Statistics from Results Spreadsheets (Tables) Interactive Probability Calculator T-Tests Frequency Tables, Crosstabulation Tables, Stub-and-Banner Tables, Multiple Response Analysis Multiple Regression Methods Nonparametric Statistics ANOVA Distribution Fitting
STATISTICA Multivariate Exploratory Techniques	Cluster Analysis Techniques Factor Analysis Principal Components & Classification Analysis Canonical Correlation Analysis Reliability/Item Analysis Classification Trees Correspondence Analysis Multidimensional Scaling Discriminant Analysis General Discriminant Analysis Models (GDA)
STATISTICA Advanced Linear/Non-Linear Models	Variance Components and Mixed Model ANOVA/ANCOVA Survival/Failure Time Analysis General Nonlinear Estimation (and Quick Logit/Probit Regression) Log-Linear Analysis of Frequency Tables Time Series Analysis/Forecasting Structural Equation Modeling/Path Analysis (SEPATH) General Linear Models (GLM) General Regression Models (GRM) Generalized Linear Models (GLZ) General Partial Least Squares Models (PLS)
STATISTICA Power Analysis	Brief Overview Detailed Description List of Tests
STATISTICA Neural Networks	Input Data Input Selection and Dimensionality Reduction Data Scaling and Nominal Value Preparation Selecting a Neural Network Model The Intelligent Problem Solver (an easy-to-use wizard for network creation) Training a Neural Network Probing and Testing a Neural Network Network Editing, Modification, and Pipe-lining Embedded Solutions Training Algorithm Summary Platforms System Requirements Size Limitations Electronic Manual
STATISTICA Quality Control Charts	Input Data Input Selection and Dimensionality Reduction Data Scaling and Nominal Value Preparation Selecting a Neural Network Model The Intelligent Problem Solver (an easy-to-use wizard for network creation) Training a Neural Network Probing and Testing a Neural Network Network Editing, Modification, and Pipe-lining Embedded Solutions Training Algorithm Summary Platforms System Requirements Size Limitations Electronic Manual
STATISTICA Process Analysis	Process capability analysis Designs for Gage Repeatability/Reproducibility (R&R) Analyses. Weibull analysis Sampling plans
STATISTICA Design of Experiments	Design of Experiments Analysis of experiments: General features Residual analyses and transformations Optimization of single or multiple response variables: The response (desirability) profiler Standard two-level 2**(k-p) fractional factorial designs with blocks (Box-Hunter-Hunter minimum aberration designs). Minimum aberration and maximum unconfounding 2**(k-p) fractional factorial designs with blocks: General design search Screening (Plackett-Burman) designs Mixed-level factorial designs Three-level 3**(k-p) fractional factorial designs with blocks and Box-Behnken designs Central composite (response surface) designs Latin squares Taguchi robust design experiments Designs for mixtures and triangular graphs Designs for constrained surfaces and mixtures D- and A-optimal designs Alternative procedures for analyzing data collected in experiments
STATISTICA QC Miner	Summary Go Beyond Simple Quality Control: Don't Just React to Problems, ANTICIPATE Them! Solution Packages for Specific Needs How it Works Customize all Projects using Industry Standard In-place Database Processing Using STATISTICA QC Miner as a Silent Monitor and Learner
STATISTICA Data Miner	Data Mining Tools General Slicer/Dicer and Drill-Down Explorer General Classifier General Modeler/Multivariate Explorer General Forecaster General Neural Networks Explorer Specialized Data Mining Modules Feature Selection and Variable Filtering Association Rules Interactive Drill-Down Explorer Generalized EM & k-Means Cluster Analysis Generalized Additive Models General Classification and Regression Trees General CHAID Models Interactive Classification and Regression Trees Boosted Trees Multivariate Adaptive Regression Splines Goodness of Fit Computations Rapid Deployment of Predictive Models
STATISTICA Text Miner	Accessing Documents Processing Documents Analyzing Documents