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STATISTICA is Integrated with Borden Chemical's Data Repositories & Automates Report Publishing for Internal Audiences and Borden's Customers

Borden Chemical is a leading supplier of high-performance resins, adhesives, coatings, and basic chemicals to a broad range of industries. Borden Chemical's products provide sticking and bonding power and other performance enhancements for thousands of end-use applications, including: wood composites and other building materials; foundry molds and cores; fiber-optic cabling; electronics; enhanced oilfield production; and automotive and aerospace components.

STATISTICA Enterprise-wide SPC System (SEWSS) is used at Borden Chemical as an analysis platform at over 30 sites worldwide, providing comprehensive data analysis and reporting tools for over 150 researchers, Quality Control engineers, and technical consultants. The powerful report generation features in SEWSS automate product test data analysis and create monthly product reviews and reports sent to customers with product shipments.

Borden Chemical also utilizes SEWSS for ongoing monitoring of production process data, the design and analysis of research studies to optimize product formulations, and the ad hoc troubleshooting of manufacturing issues.

To read the entire application story, click here.



Solar Turbines: Gas Turbine and Remote Monitoring and Diagnostics (Diesel & Gas Turbine Worldwide)

A recent article published in Diesel and Gas News describes how StatSoft's STATISTICA Enterprise-wide SPC System (SEWSS) has been incorporated into the customized Remote Integrated Services program at Solar Turbines, a world leading producer of mid-range industrial gas turbines. With the new remote monitoring and diagnostics program in place, significant savings are expected in "decreased downtime, reduced staffing and, ultimately, engine life extension."

Data filtration and analysis time are reduced at Solar Turbines with the remote monitoring and diagnostics program's centralized database, in which data is automatically filtered and trending and assessment are automated with a rule-based diagnostic software program. Engine operations are monitored live via the Web and automated engineering reports are generated daily and delivered electronically to Solar Turbines' secure Web site, in which multiple users have different access privileges.

Click here to read the entire case study.





STATISTICA Seminar Series:
             Webcasts for Current and Prospective STATISTICA Users

The STATISTICA Seminar Series provides a convenient, Web-based means to learn about STATISTICA features and their applications. Representative topics include demonstrations of a specific STATISTICA product or solutions provided for an industry-specific application.

Registration for each seminar is required for attendance. Space is limited. If you identify one or more seminars in which you would like to participate, click on the link to Register. A StatSoft representative will contact you with a registration confirmation that includes the necessary details to attend the seminar.

Customized Web-based Analytic Applications using WebSTATISTICA
Date: April 22, 2004, 11:00 a.m. - 12:00 p.m. CST
Presenter: Thomas Hill, Ph.D., Vice President for Analytic Procedures Development

LIMS Data Unleashed: STATISTICA for R&D and QC Applications
Date: April 30, 2004, 11:00 a.m. - 12:00 p.m. CST
Presenter: Robert Eames, Product Manager

STATISTICA Data Miner: Discover Opportunities for Predictive Analytics and Knowledge Discovery Applications
Date: May 6, 2004, 11:00 a.m. - 12:00 p.m. CST
Presenter: Thomas Hill, Ph.D., Vice President for Analytic Procedures Development

STATISTICA: A Collaborative Analytics Platform for Research and Development Organizations
Date: May 7, 2004, 11:00 a.m. - 12:00 p.m. CST
Presenter: Robert Eames, Product Manager

STATISTICA for Validated Applications in Regulated Industries
Date: May 14, 2004, 11:00 a.m. - 12:00 p.m. CST
Presenter: Robert Eames, Product Manager

Click here for more information on these topics.
Register for one or more of the upcoming Webcasts.

Exhibitions

Business Improvement Through Statistical Thinking - Organised by the Royal Statistical Society
Britannia Royal Court Hotel, Keresley, Coventry, UK
April 21-22, 2004

27th PSI Annual Conference
Carden Park, Cheshire, UK
May 10, 2004

Control 2004 - 18th International Trade Fair for Quality Assurance
Sinsheim, Germany - Exhibition Centre
May 11-14, 2004
Hall 4, Booth #4316

Analytica 2004 - 19th International Trade Fair and Analytica Conference
Munich, Germany - Neue Messe
May 11-14, 2004
Hall A2, Booth A2.264

58th Annual Quality Congress
Toronto, Ontario, Canada - Metropolitan Toronto Convention Centre
May 24 - 26, 2004
Booth #207

Quality Detroit 2004
Novi, Michigan, USA - Novi Expo Center
June 9 - 10, 2004
Booth #830

Click here to view the complete list of exhibits StatSoft will attend in 2004.



STATISTICA Multivariate Statistical Process Control (MSPC) - provides a complete solution for multivariate statistical process control applicable to complex manufacturing processes. Specific features for application to process industries such as chemical, petrochemical, pharmaceutical, and pulp and paper.

STATISTICA Monitoring and Alerting Server (MAS) - provides organizations with the software and tools to centralize and automate the monitoring of many process and product parameters.

Click here for an overview of STATISTICA products.



STATISTICA Data Miner "In a Class by Itself" According to DM Review Comparison (DM Direct Special Report, March 23, 2004)

In his recent article "How to Choose a Data Mining Suite", Dr. Robert A. Nisbet reviews five popular data mining suites to help companies evaluate which suite is best for their particular needs, including STATISTICA Data Miner, SPSS-Clementine, Affinium Model, Insightful Miner, and KXEN.

Referring to his comprehensive table showing a weighted comparison of the features and functions of the different tools, Dr. Nisbet notes that by comparing the relatively moderate cost and the weighted score across all features and functions, STATISTICA Data Miner is "the clear winner" and is "in a class by itself". He goes on to state that "no data mining suite available today provides more tools for performing data mining projects" and proclaims STATISTICA Data Miner as his "personal favorite" among the tools he evaluated.

Dr. Nisbet lists the pros of STATISTICA Data Miner, including "the richest combination of parametric statistical and machine learning data mining algorithms", "highly flexible tools for model output", "powerful tools for reduction of dimensionality", and "scalability (STATISTICA Data Miner can more rapidly process larger data sets both in terms of their dimensionality and the overall size than the other products)".

Dr. Nisbet has over 30 years experience in complex systems analysis and modeling as a Research Professor (University of California, Santa Barbara) and as consultant in data mining sciences. While at NCR Corporation and Torrent Systems, he pioneered the design and development of configurable data mining applications for retail sales forecasting, and Churn, Propensity-to-buy, and Customer Acquisition in Telecommunications and Insurance.

Click here to read the complete review in pdf format.
Click here to view other STATISTICA awards, comments from users, and a complete summary of STATISTICA's unmatched record of reviews.



Feature Textbook Topic: Machine Learning

Machine Learning includes a number of advanced statistical methods for handling regression and classification tasks with multiple dependent and independent variables. These methods include Support Vector Machines (SVM) for regression and classification, Naive Bayes for classification, and k-Nearest Neighbours (KNN) for regression and classification. Detailed discussions of these techniques can be found in Hastie, Tibshirani, & Freedman (2001); a specialized comprehensive introduction to support vector machines can also be found in Cristianini and Shawe-Taylor (2000).

Support Vector Machines (SVM)
This method performs regression and classification tasks by constructing nonlinear decision boundaries. Because of the nature of the feature space in which these boundaries are found, Support Vector Machines can exhibit a large degree of flexibility in handling classification and regression tasks of varied complexities. There are several types of Support Vector models including linear, polynomial, RBF, and sigmoid.

Naive Bayes
This is a well established Bayesian method primarily formulated for performing classification tasks. Given its simplicity, i.e., the assumption that the independent variables are statistically independent, Naive Bayes models are effective classification tools that are easy to use and interpret. Naive Bayes is particularly appropriate when the dimensionality of the independent space (i.e., number of input variables) is high (a problem known as the curse of dimensionality). For the reasons given above, Naive Bayes can often outperform other more sophisticated classification methods. A variety of methods exist for modeling the conditional distributions of the inputs including normal, lognormal, gamma, and Poisson.

k-Nearest Neighbors
k-Nearest Neighbors is a memory-based method that, in contrast to other statistical methods, requires no training (i.e., no model to fit). It falls into the category of Prototype Methods. It functions on the intuitive idea that close objects are more likely to be in the same category. Thus, in KNN, predictions are based on a set of prototype examples that are used to predict new (i.e., unseen) data based on the majority vote (for classification tasks) and averaging (for regression) over a set of k-nearest prototypes (hence the name k-nearest neighbors).

Go to the Electronic Statistics Homepage for the complete textbook.





StatSoft, Inc. is pleased to announce the 2004 STATISTICA training schedule for the United States.

Featuring a variety of introductory and advanced training courses in major U.S. cities, StatSoft training classes offer:
  • Practical hands-on experience with the program
  • An introduction to real-world example applications
  • Energetic, helpful, knowledgeable instructors
  • Comprehensive take-home course manual
  • Personal attention, small class size
  • Interactive, class-paced learning

    In addition to a two day course on the Introduction to STATISTICA, StatSoft offers one day training for SPC, DOE, Multivariate Analysis, Anova/Regression, Neural Networks, Graphical Data Analysis, Visual Basic applications, and Six Sigma Statistics.

    Sign up today to enhance your knowledge and understanding of STATISTICA tools!

    Click here to view the dates and locations of courses in 2004.
    Click here to register, or email training@statsoft.com.au.

    • April 2004

    April 26-27, 2004 Introduction Tulsa, OK
    April 28, 2004 STATISTICA Neural Networks Tulsa, OK
    April 29, 2004 STATISTICA Data Miner Tulsa, OK


    May 2004

    May 18-19, 2004 Introduction Chicago, IL
    May 20, 2004 DOE Chicago, IL
    May 25-26, 2004 Introduction Tulsa, OK
    May 27, 2004 Multivariate Analysis Tulsa, OK
    May 28, 2004 GDA Tulsa, OK


    June 2004

    June 15-16, 2004 Introduction to STATISTICA for STATISTICA Data Miner users Tulsa, OK
    June 17-18, 2004 STATISTICA Data Miner Tulsa, OK
    June 22-23, 2004 Introduction Tulsa, OK
    June 24, 2004 ANOVA/Regression Tulsa, OK
    June 25, 2004 DOE Tulsa, OK


    July 2004

    July 20-21, 2004 Introduction Washington, DC
    July 22, 2004 ANOVA/Regression Washington, DC
    July 27-28, 2004 Introduction Tulsa, OK
    July 29, 2004 DOE Tulsa, OK
    July 30, 2004 SPC Tulsa, OK

    Register Now!

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