JMP (statistical software)

suite of computer programs for statistical analysis developed by the JMP business unit

JMP is computer software used for statistical analysis and machine learning. It is created by JMP, a part of SAS Institute. The name is pronounced like the word "jump".[1] The program was launched in 1989 to be used on MacOS, and can be used on MacOS and the Windows operating system. The software is used for analyzing and using data in areas like data mining, research and engineering.

JMP
Developer(s)JMP Statistical Discovery LLC
Stable release
v17.2 / March 2023
Operating systemWindows, Macintosh, Windows Server
LicenseProprietary
Websitejmp.com

History

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JMP was developed in the 1980s by John Sall and a team of programmers, to be used on the Apple Macintosh.[2][3] The name originally stood for "John's Macintosh Project".[4] It was released in October 1989.[2]

Software

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JMP includes JMP, JMP Pro, JMP Clinical and JMP Genomics,[5] and JMP Live.[6] The software has a simple menu design,[7] and shows data using visual information like graphic so that users can easily discover information.[8] It is used for designing experiments,[9] analyzing data, artificial intelligence, machine learning, and data mining.[10][11][12]

JMP can be used with the R and Python programming languages.[13]

References

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  1. SAS Institute Inc. "About JMP". Retrieved 2 July 2016.
  2. 2.0 2.1 Cox, Ian; Gaudard, Marie A.; Ramsey, Philip J.; Stephens, Mia L.; Wright, Leo (21 December 2009). Visual Six Sigma: Making Data Analysis Lean. John Wiley & Sons. p. 23. ISBN 978-0-470-50691-2. Retrieved 16 November 2012.
  3. Lai, Eric (18 September 2009). "Billionaire SAS co-founder keeps on coding". Computerworld. Archived from the original on 16 September 2017. Retrieved 29 November 2022.
  4. Lai, Eric (18 September 2009). "Billionaire SAS co-founder keeps on coding". Computerworld. Archived from the original on 3 February 2016.
  5. Taylor, James (August 10, 2011). "First Look – JMP Pro". JTonEDM. Retrieved May 31, 2012.
  6. JMP Website
  7. Castro-Schilo, Laura; Russo, Eric (March 16, 2021). "Fitting Structural Equations Models with Interactive and Dynamic Tools in JMP Pro". Structural Equation Modeling. 28 (5): 794–806. doi:10.1080/10705511.2020.1854764 – via Taylor & Francis.
  8. Jones, B.; Sall, J. (2011). "JMP statistical discovery software". Wiley Interdisciplinary Reviews: Computational Statistics. 3 (3): 188–194. doi:10.1002/wics.162. S2CID 60622844.
  9. Okerson, Barbara, JMPing In: A SAS Programmer's Look at JMP (PDF), retrieved 30 December 2012
  10. Fortino, Andres (2023-01-30). Data Mining and Predictive Analytics for Business Decisions: A Case Study Approach. Mercury Learning and Information. p. 14. ISBN 978-1-68392-673-3.
  11. Machine Learning for Business Analytics: Concepts, Techniques and Applications with JMP Pro. John Wiley & Sons. 2023. p. 39. ISBN 978-1-119-90385-7.
  12. Li, Jie; Mocko, Megan (2020-12-01). "Machine learning for a citizen data scientist: an experience with JMP". Journal of Marketing Analytics. 8 (4): 267–279. doi:10.1057/s41270-020-00092-6. ISSN 2050-3326.
  13. Abousalh-Neto, Nascif; Guan, Meijian; Hummel, Ruth (March 3, 2021). "Better together: Extending JMP® with open-source software". Stat. 10 (1). Wiley. doi:10.1002/sta4.336. ISSN 2049-1573.