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MathSoft Data Analysis Division Introduces S-PLUS® 6 for UNIX/Linux 

Major Upgrade Includes New Java-based Graphical User Interface And Connectivity

Seattle, WA—October 5, 2000— MathSoft, Inc. (NASDAQ: MATH), Data Analysis Division, a leading
provider of solutions for statistical data mining and predictive modeling technology, today introduced
S-PLUS 6 for UNIX, a major enhancement to the company’s statistical data mining software. S-PLUS 6
provides a popular software platform for business intelligence and decision support applications that
leverage state-of-the-art statistical analysis and visualization methods.

The release features a powerful new Java-based point-and-click user interface to simplify and accelerate
access, analysis, and visualization of technical and business data. A new integration method, called
CONNECT/Java, allows software developers to enhance the analytical and graphics capabilities within
their applications by embedding the S-PLUS engine. 

S-PLUS 6 offers innovative visualization capabilities including a new form of Java-based graphic, called
Graphlets™, which makes it easy to deploy interactive, drill-down graphics via Web pages.

S-PLUS includes a suite of flexible and sophisticated data display techniques to transform quantitative
information into easy to understand charts, using multiple tabbed pages. A new Java-based graphics device
allows users to export graphs in file formats such as JPEG, TIFF, PNG, PNM, and Windows BMP
formats, in addition to live Graphlets.

"S-PLUS 6’s object-oriented programming model is critical for building statistical tools for complex data
analysis. In particular, its new interface to Java provides additional tools for integrating S-based analyses
into a distributed environment where we can build Web-based reporting applications, access and analyze
relational databases, and build other analytical systems," said David James, Statistics Research, Lucent
Technologies.

"Java connectivity combined with powerful S-PLUS analytics accessible from our new user interface will
allow our customers and our consulting group to build modern business intelligence systems that help users
gain insight from their data, " said Shawn Javid, senior vice president and general manager, MathSoft Inc.
"S-PLUS 6 offers new methods for handling data including missing data and robust statistics delivering
more accurate results so decision makers and analysts can make smarter decisions."

S-PLUS 6 for UNIX will initially be available for Linux and Solaris. Versions for other UNIX platforms will
be made released over the coming months.

Key new benefits of S-PLUS 6 include:

New Java-based Graphical User Interface—Now for the first time users can access the
powerful statistical and graphing techniques of S-PLUS 6 through an intuitive, point-and-click
graphical user interface. Now, users can easily import and export data, run statistical analyses, and
create insightful graphs.

New Java Programmer Interfaces —Users can integrate S-PLUS 6 with other applications using
CONNECT/Java. The powerful suite of functions gives users the flexibility to call S-PLUS from
Java applications and call Java from S-PLUS.

New Capabilities for Linear and Nonlinear Mixed-Effects Models—Proper handling of
correlated data in linear and nonlinear regression models is critical in areas as diverse as biomedical
research, manufacturing, and market research. S-PLUS 6 incorporates the latest research by Dr.
José Pinheiro (Lucent Technologies) and Professor Douglas Bates (University of Wisconsin).
S-PLUS 6 offers the most advanced and powerful set of tools for fitting linear and nonlinear mixed
effects.

Major Upgrade of Survival Analysis Tools—This release incorporates the Version 5 release of
the Survival library by Dr. Terry Therneau of the Mayo Clinic. This includes features not found in any
other major package, including frailty models, smoothing splines, and sophisticated parametric
survival methods.

New Cutting-edge Library for Handling Missing Data—S-PLUS 6 is the only package that
lets you account for missing data values using three different multiple imputation models: Gaussian,
Logistic, and Conditional Gaussian.

New Robust Statistics Library For More Reliable Estimates—S-PLUS 6 offers the widest selection
of robust techniques for regression, covariance, and time series analysis, plus new plots for outlier detection
and a new paradigm for multiple model fits and comparisons. Gain more reliable estimates and forecasts
from imperfect data using S-PLUS.