Jmp Version - History __full__
Introduction JMP is a statistical discovery software package developed by SAS Institute. The software has a long history of providing data visualization, statistical analysis, and data mining capabilities to users. This report provides an overview of the major releases of JMP, highlighting key features and enhancements. Early Versions (1980s-1990s)
JMP 1.0 (1989) : The first version of JMP was released in 1989. It was a statistical software package developed by John Sall and a team at SAS Institute. JMP 2.0 (1991) : JMP 2.0 introduced a graphical user interface (GUI) and added support for data visualization. JMP 3.0 (1993) : JMP 3.0 included enhancements to the GUI and added new statistical features.
Major Releases (2000s-2010s)
JMP 4.0 (2000) : JMP 4.0 introduced a new user interface and added support for data mining and predictive analytics. JMP 5.0 (2003) : JMP 5.0 included enhancements to the user interface and added new features for data visualization and statistical analysis. JMP 6.0 (2005) : JMP 6.0 introduced support for scripting and automation using the JMP Scripting Language (JSL). JMP 7.0 (2007) : JMP 7.0 included enhancements to the user interface and added new features for data visualization and statistical analysis. JMP 8.0 (2009) : JMP 8.0 introduced support for 64-bit processors and added new features for data mining and predictive analytics. JMP 9.0 (2010) : JMP 9.0 included enhancements to the user interface and added new features for data visualization and statistical analysis. jmp version history
Recent Releases (2010s-present)
JMP 10.0 (2012) : JMP 10.0 introduced a new user interface and added support for big data analytics. JMP 11.0 (2014) : JMP 11.0 included enhancements to the user interface and added new features for data visualization and statistical analysis. JMP 12.0 (2016) : JMP 12.0 introduced support for R and Python integration and added new features for data mining and predictive analytics. JMP 13.0 (2018) : JMP 13.0 included enhancements to the user interface and added new features for data visualization and statistical analysis. JMP 14.0 (2020) : JMP 14.0 introduced support for modern data science workflows and added new features for data mining and predictive analytics.
Current Version
JMP 16.0 (2022) : The current version of JMP, released in 2022, includes enhancements to the user interface, new features for data visualization and statistical analysis, and improved integration with other SAS products.
Conclusion JMP has a rich history of providing data visualization, statistical analysis, and data mining capabilities to users. From its early versions to the current release, JMP has continued to evolve and improve, adding new features and enhancements to support the needs of data analysts and scientists.
From its 1989 debut on the Macintosh to the current JMP 18, the software has evolved from a visual desktop statistics tool into a predictive analytics powerhouse featuring native Python integration and "Easy DOE" workflows. Key milestones included the introduction of Graph Builder in JMP 4, R integration in JMP 9, and the launch of JMP Pro in JMP 10. You can explore the full history and feature evolution on the JMP blog. Introduction JMP is a statistical discovery software package
JMP Through the Ages: A Review of Version History In the world of statistical discovery, JMP (pronounced "jump") has carved out a unique niche since 1989. Unlike the command-line rigor of SAS or the package-heavy sprawl of R, JMP has always championed dynamic visualization and interactive exploration . Reviewing its version history is akin to watching the democratization of data analysis unfold—one linked brush and red triangle at a time. The Early Years: The Macintosh Revolution (JMP 1–3) JMP 1.0 (1989) launched exclusively for Macintosh. Developed by John Sall (co-founder of SAS Institute) and a small team, it was a radical idea: a statistical package built from the ground up for graphical user interfaces. The hallmark feature was dynamic brushing —clicking a point in a scatterplot highlighted it in all other open graphs. For the era, this was magic. JMP 2.0 (1991) added survival analysis and the beginnings of design of experiments (DOE). JMP 3.0 (1994) brought the "JMP Journal," a reproducible report format that saved graphs and scripts together—decades ahead of modern notebooks.
Verdict: These versions were niche but visionary. Mac-based statisticians loved them; everyone else was still writing SAS code.