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JMP (statistical software)
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JMP (statistical software)
JMP (pronounced "jump") is a suite of computer programs for statistical analysis and machine learning developed by JMP, a subsidiary of SAS Institute. The program was launched in 1989 to take advantage of the graphical user interface introduced by the Macintosh operating systems. It has since been significantly rewritten and made available for the Windows operating system.
The software is focused on exploratory visual analytics, where users investigate and explore data. It also supports the verification of these explorations by hypothesis testing, data mining, or other analytic methods. Discoveries made using JMP's analytical tools are commonly applied for experimental design.
JMP is used in applications such as data mining, Six Sigma, quality control, design of experiments, as well as for research in science, engineering, and social sciences. The software can be purchased in any of four configurations: JMP, JMP Pro, JMP Clinical, and JMP Live. JMP can be automated with its proprietary scripting language, JSL.
JMP was developed in the mid- to late-1980s by John Sall and a team of developers to make use of the graphical user interface introduced by the Apple Macintosh. It originally stood for "John's Macintosh Project" and was first released in October 1989. It was used mostly by scientists and engineers for design of experiments (DOE), quality and productivity support (Six Sigma), and reliability modeling. Semiconductor manufacturers were also among JMP's early adopters.
Interactive graphics and other features were added in 1991 with version 2.0, which was introduced at the 1991 Macworld Expo. Version 2 was twice the size as the original, though it was still delivered on a floppy disk. It required 2 MB of memory and came with 700 pages of documentation. Support for Microsoft Windows was added with version 3.1 in 1994. Rewritten with Version 4 and released in 2002, JMP could import data from a wider variety of data sources and added support for surface plots. Version 4 also added time series forecasting and new smoothing models, such as the seasonal smoothing method, called Winter's Method, and ARIMA (Autoregressive Integrated Moving Average). It was also the first version to support JSL, JMP Scripting Language.
In 2005, data mining tools like a decision tree and neural net were added with version 5 as well as Linux support, which was later withdrawn in JMP 9. Later in 2005, JMP 6 was introduced. JMP began integrating with SAS in version 7.0 in 2007 and has strengthened this integration ever since. Users can write SAS code in JMP, connect to SAS servers, and retrieve and use data from SAS. Support for bubble plots was added in version 7. JMP 7 also improved data visualization and diagnostics.
JMP 8 was released in 2009 with new drag-and-drop features and a 64-bit version to take advantage of advances in the Mac operating system. It also added a new user interface for building graphs, tools for choice experiments and support for Life Distributions. According to Scientific Computing, the software had improvements in "graphics, QA, ease-of-use, SAS integration and data management areas." JMP 9 in 2010 added a new interface for using the R programming language from JMP and an add-in for Excel. The main screen was rebuilt and enhancements were made to simulations, graphics and a new Degradation platform. In March 2012, version 10 made improvements in data mining, predictive analytics, and automated model building.
Version 11 was released in late 2014. It included new ease-of-use features, an Excel import wizard, and advanced features for design of experiments. Two years later, version 12.0 was introduced. According to Scientific Computing, it added a new "Modeling Utilities" submenu of tools, performance improvements and new technical features for statistical analysis. Version 13.0 was released in September 2016 and introduced various improvements to reporting, ease-of-use and its handling of large data sets in memory. Version 14.0 was released in March 2018; new functionality included a Projects file management tool alongside the ability to use your own images as markers on your graph.
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JMP (statistical software)
JMP (pronounced "jump") is a suite of computer programs for statistical analysis and machine learning developed by JMP, a subsidiary of SAS Institute. The program was launched in 1989 to take advantage of the graphical user interface introduced by the Macintosh operating systems. It has since been significantly rewritten and made available for the Windows operating system.
The software is focused on exploratory visual analytics, where users investigate and explore data. It also supports the verification of these explorations by hypothesis testing, data mining, or other analytic methods. Discoveries made using JMP's analytical tools are commonly applied for experimental design.
JMP is used in applications such as data mining, Six Sigma, quality control, design of experiments, as well as for research in science, engineering, and social sciences. The software can be purchased in any of four configurations: JMP, JMP Pro, JMP Clinical, and JMP Live. JMP can be automated with its proprietary scripting language, JSL.
JMP was developed in the mid- to late-1980s by John Sall and a team of developers to make use of the graphical user interface introduced by the Apple Macintosh. It originally stood for "John's Macintosh Project" and was first released in October 1989. It was used mostly by scientists and engineers for design of experiments (DOE), quality and productivity support (Six Sigma), and reliability modeling. Semiconductor manufacturers were also among JMP's early adopters.
Interactive graphics and other features were added in 1991 with version 2.0, which was introduced at the 1991 Macworld Expo. Version 2 was twice the size as the original, though it was still delivered on a floppy disk. It required 2 MB of memory and came with 700 pages of documentation. Support for Microsoft Windows was added with version 3.1 in 1994. Rewritten with Version 4 and released in 2002, JMP could import data from a wider variety of data sources and added support for surface plots. Version 4 also added time series forecasting and new smoothing models, such as the seasonal smoothing method, called Winter's Method, and ARIMA (Autoregressive Integrated Moving Average). It was also the first version to support JSL, JMP Scripting Language.
In 2005, data mining tools like a decision tree and neural net were added with version 5 as well as Linux support, which was later withdrawn in JMP 9. Later in 2005, JMP 6 was introduced. JMP began integrating with SAS in version 7.0 in 2007 and has strengthened this integration ever since. Users can write SAS code in JMP, connect to SAS servers, and retrieve and use data from SAS. Support for bubble plots was added in version 7. JMP 7 also improved data visualization and diagnostics.
JMP 8 was released in 2009 with new drag-and-drop features and a 64-bit version to take advantage of advances in the Mac operating system. It also added a new user interface for building graphs, tools for choice experiments and support for Life Distributions. According to Scientific Computing, the software had improvements in "graphics, QA, ease-of-use, SAS integration and data management areas." JMP 9 in 2010 added a new interface for using the R programming language from JMP and an add-in for Excel. The main screen was rebuilt and enhancements were made to simulations, graphics and a new Degradation platform. In March 2012, version 10 made improvements in data mining, predictive analytics, and automated model building.
Version 11 was released in late 2014. It included new ease-of-use features, an Excel import wizard, and advanced features for design of experiments. Two years later, version 12.0 was introduced. According to Scientific Computing, it added a new "Modeling Utilities" submenu of tools, performance improvements and new technical features for statistical analysis. Version 13.0 was released in September 2016 and introduced various improvements to reporting, ease-of-use and its handling of large data sets in memory. Version 14.0 was released in March 2018; new functionality included a Projects file management tool alongside the ability to use your own images as markers on your graph.