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Phil Kay
05-05-2025

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The results illustrated in this article are specific to the particular situations, business models, data input and computing environments described herein. Each JMP customer’s experience is unique, based on business and technical variables, and all statements must be considered nontypical. Actual savings, results and performance characteristics will vary depending on individual customer configurations and conditions. JMP does not guarantee or represent that every customer will achieve similar results. The only warranties for JMP products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with JMP as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of JMP software.

Phil Kay

Phil Kay is a learning manager for JMP Statistical Discovery, a subsidiary of SAS. His job is to understand the science and engineering challenges and provide guidance on data analytic solutions for industrial organisations around the world.

Previously, Phil was a key scientist in the development of numerous processes for the manufacture of colorants for digital printing at FujiFilm Imaging Colorants. Phil has a master’s degree in applied statistics with a dissertation on Design of Experiments. He also has a master’s and PhD in chemistry.

He is a Fellow of the Royal Statistical Society, a Chartered Chemist, and a member of the committee for the Process Chemistry and Technology Group with the Royal Society of Chemistry.

Phil loves showing people how data analytics enables better science. Follow Phil Kay, Evangelist for Data Analytics, on LinkedIn.

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