JMP, a statistical software suite originally developed as "John’s Macintosh Project" by John Sall in the late 1980s, has evolved from a niche Mac tool into a global standard for scientists and engineers. Its history is marked by a transition from a dedicated Macintosh application to a cross-platform powerhouse that became a wholly owned subsidiary of SAS in 2022. Early Origins: 1989 – 2000
JMP was first released in October 1989 to leverage the graphical user interface (GUI) of the Apple Macintosh for statistical discovery.
JMP 1.0 (1989): Designed for interactivity, allowing users to explore data visually rather than through code-heavy command lines.
JMP 2.0 (1991): Doubled in size and introduced at Macworld Expo, this version required 2MB of memory and added more interactive graphics.
JMP 3.1 (1994): A major milestone where JMP expanded beyond Apple, introducing support for Microsoft Windows. Expansion and Modernization: 2002 – 2014
As the software matured, it underwent significant architectural rewrites to support more complex data sources and advanced statistical modeling.
JMP 4 (2002): Rewritten to handle a wider variety of data imports and introduced surface plots for better visualization.
JMP 11 (2014): Focused on "ease-of-use" with the introduction of the Excel Import Wizard and advanced features for Design of Experiments (DOE). The Recent Era: JMP 12 – JMP 17 jmp version history
The last decade has seen JMP transition toward larger datasets, better reporting, and specialized versions like JMP Pro for advanced predictive modeling.
JMP was first launched in 1989 as a product of SAS Institute. Over the decades, it has evolved from a Macintosh-only statistical tool into a multi-platform suite used for complex data exploration and predictive modeling. 🏛️ Origins and Early Growth
1989 (Version 1): Launched by SAS co-founder John Sall to provide a visual, interactive way to explore data on the Apple Macintosh.
Version 3.1.5: An early 1990s release that ran on "Classic" Mac OS (System 9).
Version 4: Introduced the JMP Scripting Language (JSL), allowing users to automate analysis and build custom applications. 🚀 Major Modern Milestones How to open data files from earlier versions?
Version 10 marked the introduction of the JMP Pro edition, creating a tiered product. Standard JMP for general analytics; JMP Pro for cross-validation, advanced modeling, and huge data.
Pro Features:
Standard Features:
Celebrating two decades, JMP 8 focused on sharing results and scripting.
Key Additions:
JMP 7 was a visual renaissance. The software shed its "1990s Mac look" and adopted a modern, docked interface with tabbed documents, directly competing with SPSS 16 and Minitab 15.
Headline Features:
JMP 12 was a love letter to the reliability engineer. It added robust functional data analysis tools.
Notable Features:
By 2010, "Big Data" was a buzzword. JMP 9 responded with significant performance upgrades.
What's New:
JMP 13.0 (2016) is a fan favorite. It added Functional Data Explorer (for curves, spectra, profiles), Graph Spawning (right-click any graph to get related views), and Precision Binning for histograms. The Project container finally allowed organizing multiple windows into one file.
JMP 14.0 (2018) doubled down on pre-processing: Interactive Missing Value Imputation, Recurrence Analysis, and Python integration (call Python scripts, use pandas dataframes). The reliability and survival analysis platforms also matured significantly.
Verdict: JMP 13/14 felt like a mature IDE for data exploration. If you used older versions, these were the most polished releases up to that point.
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.