JMP (statistical software)

Last updated

JMP
Developer(s) JMP Statistical Discovery LLC
Stable release
v17.2 / March 2023
Operating system Windows, Macintosh, Windows Server
Type Statistical package, visualization, multivariate analysis, genomics, biomarkers, clinical
License Proprietary
Website jmp.com

JMP (pronounced "jump" [1] ) 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.

Contents

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 five configurations: JMP, JMP Pro, JMP Clinical, JMP Genomics and JMP Live. JMP can be automated with its proprietary scripting language, JSL.

History

Version 1.0 of JMP from 1989 Version 1.0 of JMP 1989.png
Version 1.0 of JMP from 1989

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. [2] [3] It originally stood for "John's Macintosh Project" [4] [5] and was first released in October 1989. [2] It was used mostly by scientists and engineers for design of experiments (DOE), quality and productivity support (Six Sigma), and reliability modeling. [6] Semiconductor manufacturers were also among JMP's early adopters. [7]

Interactive graphics and other features were added in 1991 [8] [9] with version 2.0, which was introduced at the 1991 Macworld Expo. [10] 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. [11] Support for Microsoft Windows was added with version 3.1 in 1994. [5] [12] Rewritten with Version 4 and released in 2002, JMP could import data from a wider variety of data sources [13] and added support for surface plots. [9] 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. [14]

In 2005, data mining tools like a decision tree and neural net were added with version 5 [15] as well as Linux support, which was later withdrawn in JMP 9. [6] Later in 2005, JMP 6 was introduced. [7] [16] 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. [6] [17] JMP 7 also improved data visualization and diagnostics. [18]

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. [19] It also added a new user interface for building graphs, tools for choice experiments and support for Life Distributions. [20] According to Scientific Computing, the software had improvements in "graphics, QA, ease-of-use, SAS integration and data management areas." [21] JMP 9 in 2010 added a new interface for using the R programming language from JMP and an add-in for Excel. [22] [23] The main screen was rebuilt and enhancements were made to simulations, graphics and a new Degradation platform. [24] In March 2012, version 10 made improvements in data mining, predictive analytics, and automated model building. [25] [26]

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. [27] 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. [28] 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. [29] [30] 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. [31]

JMP was originally developed by a business unit of SAS Institute. As of 2011, it had 180 employees and 250,000 users. [26] In January 2021, JMP Statistical Discovery, LLC became a wholly owned subsidiary of SAS. [32]

JMP released new structural equation modeling software in the 2020s in version 15.2. [33] In March 2021, JMP introduced version 16 of JMP software, which improved structural equation modeling and added features to help determine the best model to use for the data being analyzed. [34] [35] JMP/JMP Pro 17 were released in October 2022. [36]

JMP 18 and JMP Pro 18 are scheduled for release in early 2024. [37]

Software

Screenshot of different data displays in JMP JMP data displays.png
Screenshot of different data displays in JMP

JMP consists of JMP, JMP Pro, JMP Clinical and JMP Genomics, [26] and JMP Live. [38] It formerly included the Graph Builder iPad App. [39] JMP Clinical and JMP Genomics combine JMP with SAS software. [26]

The software has a simple menu design, with information organized across either multiple windows or under multiple tabs within a single window. [40] Additional contextual menus are generated with new output. [41] The software's primary applications are for designed experiments and analyzing statistical data from industrial processes. [7] JMP can be used in conjunction with the R and Python open source programming languages to access features not available in JMP itself. [42]

JMP software is partly focused on exploratory data analysis and visualization. It is designed for users to investigate data to learn something unexpected, as opposed to confirming a hypothesis. [5] [26] [43] JMP links statistical data to graphics representing them, so users can drill down or up to explore the data and various visual representations of it. [13] [44] [45] When users interact with graphical objects, corresponding points in other tables will be updated accordingly. [41] For example, a user can select points on a graph and compare it to corresponding points on the data table, to facilitate the discovery of hidden structures within the data set. [46]

JMP has a range of capabilities related to artificial intelligence and intuitive machine learning, including support for the creation of models that incorporate predictive modelling techniques such as neural networks, advanced regression, and decision tree learning. [47]

It is a desktop application with a wizard-based user interface, while SAS can be installed on servers. [26] According to a review in Pharmaceutical Statistics, JMP is often used as a graphical front-end for a SAS system, which performs the statistical analysis and tabulations. [48] JMP Pro is intended for data scientists, and has an emphasis on advanced predictive modelling and model selection. [41] JMP Genomics, used for analyzing and visualizing genomics data, [49] requires a SAS component to operate and can access SAS/Genetics and SAS/STAT procedures or invoke SAS macros. [48] JMP Clinical, used for analyzing clinical trial data, can package SAS code within the JSL scripting language and convert SAS code to JMP. [50]

JMP Scripting Language (JSL)

The JMP Scripting Language (JSL) is an interpreted language for recreating analytic results and for automating or extending the functionality of JMP software. [51] : 29  JSL was first introduced in JMP version 4 in 2000. [52] : 1  JSL has a LISP-like syntax, structured as a series of expressions. All programming elements, including if-then statements and loops, are implemented as JSL functions. Data tables, display elements and analyses are represented by objects in JSL that are manipulated with named messages. Users may write JSL scripts to perform analyses and visualizations not available in the point-and-click interface or to automate a series of commands, such as weekly reports. [51] SAS, Python, R, and Matlab code can also be executed using JSL. [53]

Notable applications

JMP is used for analytics, predictive modelling, machine learning, and data mining in various industries. [54] [55]

Chemical engineering

JMP is used in the chemical industry for applications such as chemometrics, [56] [57] and design of experiments, including response surface methodology. [58] [59] It is commonly used by chemical engineers as it contains multiple linear regression algorithms that work in tandem with its experimental design software. [60]

Electronics

JMP is used in electronics manufacturing, [36] especially in areas such as semiconductor device modeling. [61] [62]

Environmental sciences

JMP being used in the WildTrack FIT system Wildtrack FIT JMP.png
JMP being used in the WildTrack FIT system

In 2007, a wildlife monitoring organization, WildTrack, started using JMP with the Footprint Identification Technology (FIT) system to identify individual endangered animals by their footprints. [63] [64] In 2009, the Chicago Botanic Garden used JMP to analyze DNA data from tropical breadfruit. Researchers determined that the seedless, starchy fruit was created by the deliberate hybridization of two fruits, the breadnut and the dugdug. [65]

Pharmaceutical

JMP has wide applications for the pharmaceutical industry in areas like molecular modelling, [66] quality by design, [67] statistical process control, [68] [69] and design of experiments. [70] The software is used in pharmaceutical development by companies such as Eli Lilly [71] and Regeneron Pharmaceuticals. [36]

Health care and life sciences

JMP Clinical and JMP Genomics are both widely used in medical research and bioscience. [46] The Herzenberg Laboratory at Stanford has integrated JMP with the Fluorescence Activated Cell Sorter (FACS). The FACS system is used to study HIV, cancer, stem-cells and oceanography. [72]

JMP Pro is also used by research consortium Target Malaria in Europe and Africa through a license with its lead institution, Imperial College London. Increased access to the tool has since contributed to a significant streamlining of research on several fronts: helping research teams standardize around best practices, facilitating more seamless sharing of data sets, providing a platform for visual exploratory analysis, and making possible advanced analyses that researchers were not able to perform with open-source software. [73]

See also

Related Research Articles

Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable, i.e., multivariate random variables. Multivariate statistics concerns understanding the different aims and background of each of the different forms of multivariate analysis, and how they relate to each other. The practical application of multivariate statistics to a particular problem may involve several types of univariate and multivariate analyses in order to understand the relationships between variables and their relevance to the problem being studied.

Psychological statistics is application of formulas, theorems, numbers and laws to psychology. Statistical methods for psychology include development and application statistical theory and methods for modeling psychological data. These methods include psychometrics, factor analysis, experimental designs, and Bayesian statistics. The article also discusses journals in the same field.

Data mining is the process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information from a data set and transforming the information into a comprehensible structure for further use. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD. Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating.

<span class="mw-page-title-main">SPSS</span> Statistical analysis software

SPSS Statistics is a statistical software suite developed by IBM for data management, advanced analytics, multivariate analysis, business intelligence, and criminal investigation. Long produced by SPSS Inc., it was acquired by IBM in 2009. Versions of the software released since 2015 have the brand name IBM SPSS Statistics.

<span class="mw-page-title-main">SAS Institute</span> American IT and analytics company

SAS Institute is an American multinational developer of analytics and artificial intelligence software based in Cary, North Carolina. SAS develops and markets a suite of analytics software, which helps access, manage, analyze and report on data to aid in decision-making. The company's software is used by most of the Fortune 500.

<span class="mw-page-title-main">Exploratory data analysis</span> Approach of analyzing data sets in statistics

In statistics, exploratory data analysis (EDA) is an approach of analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling and thereby contrasts traditional hypothesis testing. Exploratory data analysis has been promoted by John Tukey since 1970 to encourage statisticians to explore the data, and possibly formulate hypotheses that could lead to new data collection and experiments. EDA is different from initial data analysis (IDA), which focuses more narrowly on checking assumptions required for model fitting and hypothesis testing, and handling missing values and making transformations of variables as needed. EDA encompasses IDA.

<span class="mw-page-title-main">SAS (software)</span> Statistical software

SAS is a statistical software suite developed by SAS Institute for data management, advanced analytics, multivariate analysis, business intelligence, criminal investigation, and predictive analytics. SAS' analytical software is built upon artificial intelligence and utilizes machine learning, deep learning and generative AI to manage and model data. The software is widely used in industries such as finance, insurance, health care and education.

SUDAAN is a proprietary statistical software package for the analysis of correlated data, including correlated data encountered in complex sample surveys. SUDAAN originated in 1972 at RTI International. Individual commercial licenses are sold for $1,460 a year, or $3,450 permanently.

StatSoft is the original developer of Statistica. Dell acquired it in March 2014. Statistica is an analytics software portfolio that provides enterprise and desktop software for statistics, data analysis, data management, data visualization, data mining, which is also called predictive analytics and quality control.

Statistica is an advanced analytics software package originally developed by StatSoft and currently maintained by TIBCO Software Inc. Statistica provides data analysis, data management, statistics, data mining, machine learning, text analytics and data visualization procedures.

<span class="mw-page-title-main">Orange (software)</span> Open-source data analysis software

Orange is an open-source data visualization, machine learning and data mining toolkit. It features a visual programming front-end for explorative qualitative data analysis and interactive data visualization.

<span class="mw-page-title-main">Data and information visualization</span> Visual representation of data

Data and information visualization is the practice of designing and creating easy-to-communicate and easy-to-understand graphic or visual representations of a large amount of complex quantitative and qualitative data and information with the help of static, dynamic or interactive visual items. Typically based on data and information collected from a certain domain of expertise, these visualizations are intended for a broader audience to help them visually explore and discover, quickly understand, interpret and gain important insights into otherwise difficult-to-identify structures, relationships, correlations, local and global patterns, trends, variations, constancy, clusters, outliers and unusual groupings within data. When intended for the general public to convey a concise version of known, specific information in a clear and engaging manner, it is typically called information graphics.

<span class="mw-page-title-main">EViews</span>

EViews is a statistical package for Windows, used mainly for time-series oriented econometric analysis. It is developed by Quantitative Micro Software (QMS), now a part of IHS. Version 1.0 was released in March 1994, and replaced MicroTSP. The TSP software and programming language had been originally developed by Robert Hall in 1965. The current version of EViews is 13, released in August 2022.

<span class="mw-page-title-main">John Sall</span>

John P. Sall is an American billionaire businessman and computer software developer, who co-founded SAS Institute and created the JMP statistical software.

The SAS language is a fourth-generation computer programming language used for statistical analysis, created by Anthony James Barr at North Carolina State University. Its primary applications include data mining and machine learning. The SAS language runs under compilers such as the SAS System that can be used on Microsoft Windows, Linux, UNIX and mainframe computers.

<span class="mw-page-title-main">SPSS Modeler</span> Data analytics software

IBM SPSS Modeler is a data mining and text analytics software application from IBM. It is used to build predictive models and conduct other analytic tasks. It has a visual interface which allows users to leverage statistical and data mining algorithms without programming.

Eureqa was a proprietary modeling engine created in Cornell's Artificial Intelligence Lab and later commercialized by Nutonian, Inc. The software used genetic algorithms to determine mathematical equations that describe sets of data in their simplest form, a technique referred to as symbolic regression.

The High-performance Integrated Virtual Environment (HIVE) is a distributed computing environment used for healthcare-IT and biological research, including analysis of Next Generation Sequencing (NGS) data, preclinical, clinical and post market data, adverse events, metagenomic data, etc. Currently it is supported and continuously developed by US Food and Drug Administration, George Washington University, and by DNA-HIVE, WHISE-Global and Embleema. HIVE currently operates fully functionally within the US FDA supporting wide variety (+60) of regulatory research and regulatory review projects as well as for supporting MDEpiNet medical device postmarket registries. Academic deployments of HIVE are used for research activities and publications in NGS analytics, cancer research, microbiome research and in educational programs for students at GWU. Commercial enterprises use HIVE for oncology, microbiology, vaccine manufacturing, gene editing, healthcare-IT, harmonization of real-world data, in preclinical research and clinical studies.

References

  1. ↑ SAS Institute Inc. "About JMP" . Retrieved 2 July 2016.
  2. 1 2 Ian Cox; Marie A. Gaudard; Philip J. Ramsey; Mia L. Stephens; Leo Wright (21 December 2009). Visual Six Sigma: Making Data Analysis Lean. John Wiley & Sons. pp. 23–. ISBN   978-0-470-50691-2 . Retrieved 16 November 2012.
  3. ↑ Lai, Eric (2009-09-18). "Billionaire SAS co-founder keeps on coding". Computerworld. Retrieved 2022-11-29.
  4. ↑ Billionaire SAS co-founder keeps on coding
  5. 1 2 3 Shipp, Charles (2012). "Proficiency in JMP®Visualization" (PDF). Retrieved November 27, 2013.
  6. 1 2 3 Okerson, Barbara, JMPing In: A SAS Programmer's Look at JMP (PDF), SESUG 2011, retrieved December 30, 2012{{citation}}: CS1 maint: location (link)
  7. 1 2 3 Collins, John (September 23, 2005). "Software Innovator helps companies get the facts straight". The Irish Times. p. 8.
  8. ↑ APICS, the Performance Advantage. American Production and Inventory Control Society. 1991. Retrieved 30 December 2012.
  9. 1 2 Goodman, Arnold (January 24, 2012). "JCGS@20, Visual@40, Interface@45 & !!Challenges!!". Journal of Computational and Graphical Statistics. 20 (4): 818–829. doi:10.1198/jcgs.2011.204c. S2CID   121161909.
  10. ↑ Mace, Scott (1991-08-05). Stat visualization package adds business graphs. InfoWorld Media Group, Inc. p. 16.{{cite book}}: CS1 maint: date and year (link)
  11. ↑ Kim, Ki (1992). "JMP, Version 2. Software for Statistical Visualization on the Apple Macintosh". Journal of Chemical Information and Modeling. 32 (2): 174–175. doi:10.1021/ci00006a600. ISSN   1549-9596.
  12. ↑ John P. Sall, Northern Illinois University, archived from the original on December 5, 2012, retrieved November 16, 2012
  13. 1 2 Altman, Micah (2002). "A Review of JMP 4.03 With Special Attention to its Numerical Accuracy". The American Statistician. 56 (1): 72–75. doi:10.1198/000313002753631402. ISSN   0003-1305. S2CID   123511478.
  14. ↑ Gjertsen, Bill, Using JMP Version 4 for Time Series Analysis (PDF), North Carolina State University, retrieved December 30, 2012
  15. ↑ "What Is A Data Mining Product?". Information Management.
  16. ↑ Sall, John, JMP Version 6 Featuring Split Plots (PDF), SUGI 30, retrieved December 30, 2012{{citation}}: CS1 maint: location (link)
  17. ↑ Huisden, Robert (2011), JMP Clinical for the Exploration of Legacy Studies (PDF), archived from the original (PDF) on December 17, 2015, retrieved December 30, 2012
  18. ↑ Wass, John. "JMP7: One of the best just got better". Scientific Computing. Archived from the original on November 16, 2011. Retrieved May 9, 2012.
  19. ↑ "Launches SAS JMP 8 for Mac and Linux". Ti Journal. April 11, 2009. Retrieved December 30, 2012.
  20. ↑ "Introducing JMP Version 8" (PDF), A Technical Publication for JMP Users, no. 25, JMPer Cable, Winter 2009, archived from the original (PDF) on April 8, 2018, retrieved December 30, 2012
  21. ↑ Wass, John. "JMP 8: Continuous Improvement". Scientific Computing. Archived from the original on November 28, 2011. Retrieved November 16, 2012.
  22. ↑ New Features in JMP 9 (PDF), JMP, retrieved December 30, 2012
  23. ↑ Bridgewater, Adrian (November 3, 2010). "JMP Genomics 5: Data Visualization & Exploration". Dr. Dobb's Journal. Retrieved May 31, 2012.
  24. ↑ Wass, John. "JMP 9: A really new version". Scientific Computing. Archived from the original on September 14, 2011. Retrieved May 9, 2012.
  25. ↑ Shipp, Charles; Lafler, Kirk Paul, "Proficiency in JMP Visualization" (PDF), PharmaSUG 2012, retrieved December 30, 2012
  26. 1 2 3 4 5 6 Taylor, James (August 10, 2011). "First Look – JMP Pro". JTonEDM. Retrieved May 31, 2012.
  27. ↑ Wass, John (November 7, 2014). "JMP 11: Remarkable Statistics, Graphics and Integration". Scientific Computing. Retrieved May 11, 2016.
  28. ↑ Wass, John (January 27, 2016). "JMP Pro 12: The Best Keeps Getting Better!". Scientific Computing. Retrieved May 11, 2016.
  29. ↑ on (November 10, 2016). "First Look: SAS JMP 13 and JMP Pro 13". JT on EDM — James Taylor on Everything Decision Management. Retrieved November 28, 2016.
  30. ↑ Report, Impact; Roy, Krishna. "SAS JMP gets self-service data and text prep and analysis makeover". 451 Research. Retrieved November 28, 2016.
  31. ↑ "Top 5 Features in JMP 14 | Prism". prismtc.co.uk. Retrieved 2023-03-06.
  32. ↑ "About Us". www.jmp.com. Archived from the original on 2022-12-16. Retrieved 2024-05-02.
  33. ↑ Gonzales, Joseph E. (January 2, 2021). "Structural Equation Modeling with JMP® Pro". Measurement: Interdisciplinary Research and Perspectives. 19 (1). Informa UK Limited: 80–92. doi:10.1080/15366367.2020.1809231. ISSN   1536-6367. S2CID   232059504.
  34. ↑ JMP (March 23, 2021). "New version of JMP and JMP Pro delivers more efficient analytics". PR Newswire. Retrieved March 31, 2021.
  35. ↑ 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). Informa UK Limited: 794–806. doi:10.1080/10705511.2020.1854764. ISSN   1070-5511. S2CID   233695928.
  36. 1 2 3 "SAS Announces Latest Versions of JMP Statistical Products". Datanami. Retrieved 2024-02-24.
  37. ↑ "New in JMP 18 and JMP Pro 18 for Academics". JMP.com. April 17, 2023.
  38. ↑ JMP Website
  39. ↑ JMP Graph Builder for iPad, SAS Institute, retrieved December 30, 2012
  40. ↑ Castro-Schilo, Laura; Russo, Eric (March 16, 2021). "Fitting Structural Equations Models with Interactive and Dynamic Tools in JMP Pro". Structural Equation Modeling: A Multidisciplinary Journal. 28 (5): 794–806 – via Taylor & Francis.
  41. 1 2 3 Alex Yu, Chong Ho (2022). Data Mining and Exploration: From Traditional Statistics to Modern Data Science. CRC Press. pp. 54–55.
  42. ↑ 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.
  43. ↑ "SAS JMP 8 for the Macintosh review". Macstats. Retrieved November 19, 2012.
  44. ↑ 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.
  45. ↑ Robert H. Carver (30 July 2010). Practical Data Analysis with Jmp. SAS Institute. pp. 61–. ISBN   978-1-60764-475-0 . Retrieved 16 November 2012.
  46. 1 2 Sacerdoti, Francesco M.; Giordano, Antonio; Cavaliere, Carlo (2016-08-23). Advanced Imaging Techniques in Clinical Pathology. Humana Press. pp. 35–36. ISBN   978-1-4939-3469-0.
  47. ↑ 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.
  48. 1 2 Lovell, David P. (2011). "Review of JMP genomics". Pharmaceutical Statistics. 10 (4): 384–392. doi:10.1002/pst.460. ISSN   1539-1604. S2CID   122346429.
  49. ↑ Zhang, Qingyu; Richard S. Segall (2009). "Commercial Data Mining Software". Computational Statistics. pp. 1245–1268. doi:10.1007/978-0-387-09823-4_65. ISBN   978-0-387-09822-7.
  50. ↑ Huisden, Robert (2011), JMP Clinical for the Exploration of Legacy Studies (PDF), archived from the original (PDF) on December 17, 2015, retrieved December 30, 2012
  51. 1 2 SAS Publishing (1 March 2012). Jmp 10 Scripting Guide. SAS Institute. ISBN   978-1-61290-195-4 . Retrieved 13 December 2012.
  52. ↑ Wendy Murphrey; Rosemary Lucas (26 August 2009). Jump Into Jmp Scripting. SAS Institute. ISBN   978-1-59994-658-0 . Retrieved 14 December 2012.
  53. ↑ Publishing SAS Publishing; SAS Institute (December 11, 2009). JMP Release 8 User Guide. SAS Institute. pp. 392–. ISBN   978-1-60764-301-2 . Retrieved 13 December 2012.
  54. ↑ Fortino, Andres (2023-01-30). Data Mining and Predictive Analytics for Business Decisions: A Case Study Approach. Mercury Learning and Information. p. 14.
  55. ↑ Machine Learning for Business Analytics: Concepts, Techniques and Applications with JMP Pro. John Wiley & Sons. 2023. p. 39.
  56. ↑ Hanrahan, Grady (2008-11-21). Environmental Chemometrics: Principles and Modern Applications. CRC Press. pp. 58–59. ISBN   978-1-4200-6797-2.
  57. ↑ Brown, Steven; Tauler, Roma; Walczak, Beata (2020-05-26). Comprehensive Chemometrics: Chemical and Biochemical Data Analysis. Elsevier. p. 458. ISBN   978-0-444-64166-3.
  58. ↑ Pardo, Scott A. (2016-07-19). Empirical Modeling and Data Analysis for Engineers and Applied Scientists. Springer. p. 236. ISBN   978-3-319-32768-6.
  59. ↑ Gupta, Bhisham C.; Guttman, Irwin (2014-03-06). Statistics and Probability with Applications for Engineers and Scientists. John Wiley & Sons. p. 766. ISBN   978-1-118-52220-2.
  60. ↑ Albright, Lyle (2008-11-20). Albright's Chemical Engineering Handbook. CRC Press. ISBN   978-0-8247-5362-7.
  61. ↑ Seo, Seongmin; Song, Yong-Won (June 30, 2021). "A Study on the Safe Hydrogen Exhaust Method in the Semiconductor Industry" (PDF). Asia-Pacific Journal of Convergent Research Interchange. 7 (6).
  62. ↑ Wei, TK; Mahmud, MN (2019). "Optimization of Semiconductor Device Packaging Singulation Process". IOP Conference Series: Materials Science and Engineering. doi:10.1088/1757-899X/530/1/012020 – via iopscience.iop.org.
  63. ↑ Hayes Weier, Mary (June 25, 2007). "Scientists use BI Software and Intuit Trackers to Gauge Polar Bear Populations". InformationWeek. Archived from the original on January 26, 2013. Retrieved May 25, 2012.
  64. ↑ Duke University (December 21, 2017). "Using footprints to identify and monitor giant pandas in the wild". Phys.org. Retrieved March 31, 2021.
  65. ↑ Lai, Eric (September 18, 2009). "Billionaire SAS co-founder keeps on coding". Computerworld. Retrieved May 13, 2016.
  66. ↑ Lipkowitz, Kenny B.; Boyd, Donald B. (2009-09-22). Reviews in Computational Chemistry, Volume 7. John Wiley & Sons. p. 333. ISBN   978-0-470-12611-0.
  67. ↑ Beg, Sarwar; Hasnain, Md Saquib (2019-03-27). Pharmaceutical Quality by Design: Principles and Applications. Academic Press. ISBN   978-0-12-816372-6.
  68. ↑ Kenett, Ron S.; Zacks, Shelemyahu (2021-04-28). Modern Industrial Statistics: With Applications in R, MINITAB, and JMP. John Wiley & Sons. pp. 349–360. ISBN   978-1-119-71492-7.
  69. ↑ Burdick, Richard K.; LeBlond, David J.; Pfahler, Lori B.; Quiroz, Jorge; Sidor, Leslie; Vukovinsky, Kimberly; Zhang, Lanju (2017-02-14). Statistical Applications for Chemistry, Manufacturing and Controls (CMC) in the Pharmaceutical Industry. Springer. p. 6. ISBN   978-3-319-50186-4.
  70. ↑ Hinkelmann, Klaus (2012-02-14). Design and Analysis of Experiments, Volume 3: Special Designs and Applications. John Wiley & Sons. p. 394. ISBN   978-0-470-53068-9.
  71. ↑ "Advocating for Analytics: An interview with Chao Richard Li of Eli Lilly". www.jmp.com. Retrieved 2024-02-26.
  72. ↑ "Advancements in FACS System for Clinical Studies". The Computerworld Honors Program. Archived from the original on November 5, 2011. Retrieved December 15, 2011.
  73. ↑ "User Story: A major milestone towards malaria control". www.jmp.com. Retrieved 2024-05-02.

Further reading

This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.