Latest JMP® release speeds statistical discovery
Big data no problem; users can build graphs with mobile app
CARY, NC (20 Mar. 2012) – JMP ® statistical discovery software is now more powerful and intuitive, and much faster ̶ even with big data. Plus, JMP users can perform analyses on the iPad® using the JMP Graph Builder charting app. JMP Pro , version 10 – from business analytics leader SAS – offers advanced predictive modeling, model comparison and one-click bootstrapping.
"JMP 10's new capabilities make it more competitive, applicable to a wider audience and faster," said John Sall, Executive Vice President of SAS and head of SAS' JMP business unit. "When it's faster and easier, you discover more and make decisions faster."
With JMP 10, organizations can:
Visualize data more efficiently: Explore data with drag-and-drop using Graph Builder, which lets users easily switch graph types.
Sort and filter data quickly: Interchange data columns without having to repeat analyses; locally filter data by categories without affecting open reports or tables.
Perform advanced quality and reliability analyses: Drag and drop variables to build process control charts interactively; enhance reliability analyses with forecast and growth models; assess variation in measurement systems and gauges using the Measurement Systems Analysis platform.
Fit advanced statistical models easily: Fit curves to data without having to pre-impute formulas or start values using the extensive library of nonlinear models. A greatly improved partial least squares (PLS) regression capability includes a rich set of graphs and reports.
Improve experiment design: Enhance design of experiments with new features as well as a new Evaluate Design for any JMP data table treated as a design.
Extend JMP capabilities: Develop custom analytical applications with the Application Builder; distribute custom add-ins easily using Add-In Builder; improve script development with a new debugger and editor featuring a built-in log.
Add advanced predictive modeling: Conduct predictive modeling with cross-validation, exact measures of association, new one-click bootstrapping and advanced model comparison features in JMP Pro, version 10.
What users are saying about JMP 10:
"I love the Control Chart Builder! It is a very useful tool for visualizing process data! You all knocked it out of the park!" -- Jason Wiggins, Senior Research Engineer, US Synthetic
"Having one-click bootstrapping in JMP Pro seems like a great idea to me. I see this making a big difference both in practice and in the classroom. Once you get used to the one-click process, you can really go faster and be a lot more effective." -- Bradley Efron, Max H. Stein Professor of Humanities and Sciences, Professor of Statistics, Stanford University
"Application Builder is a great tool. It will open up scripting to a lot of people who want to take advantage of scripting but don't want to spend the time learning a new 'language.' Good stuff for dashboards." -- S. Jeff Heslop, Master Black Belt, GE Aviation
A fully functional 30-day trial of JMP is available free on the JMP website.
JMP, a business unit of SAS, was established in 1989 to create interactive software for desktop discovery analytics. John Sall, SAS co-founder and Executive Vice President, also heads the JMP business unit.
Graph Builder for the iPad® lets users switch from one graph to another, analyze multiple variables, and customize graphs with style and color choices.
Column Switcher in JMP 10 lets users swap out many columns in a wide data set without leaving the report.
Users can gain quick understanding of complex process data with the drag-and-drop flexibility of the Control Chart Builder in JMP 10.
In JMP 10, you can use the map size role to scale geographic regions based on the value of a variable.
The Reliability Growth platform in JMP 10 lets users model the reliability of a single repairable system over time as improvements are incorporated into the design.
Model comparison provisions in JMP Pro, version 10 enable users to compare fits across multiple fit predictions.