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Free Prism seminar – Increasing The Value Of Your Experiments With Enhanced Analytics

6 September 2016

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6 September 2016


The Trinity Centre
24 Milton Road, Cambridge , CB4 0FN United Kingdom
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Prism Training and Consultancy Ltd are to join statistical software company JMP in hosting a free seminar titled “Increasing The Value Of Your Experiments With Enhanced Analytics” at Cambridge Science Park on 6 September 2016.

Design of Experiments (DoE) is the most efficient way to empirically learn about any process or system. As the number and complexity of experiments increases you need efficient ways to ensure that you have found the most useful model from your experimental data.

Chris Challis, Business Relationship Manager, Prism:
“This event promises to be a really valuable opportunity for scientists, engineers and statisticians interested to learn about analysing designs of experiments and getting the most out of their data.”

In this special event, JMP’s Director of Statistical R&D Chris Gotwalt will talk about power tools for analysing DoEs and how you can maximize what you learn from your experiments using enhanced modelling.

The event will also include a special Q&A session in which attendees are invited to ask Chris about wider statistical methodologies.

Bernard Mckeown, JMP:
“Chris is working at the cutting edge of statistics, particularly around using analytics to improve experimental design. He works actively on some of the most challenging statistical problems that our customers face. At the same time, he is an engaging presenter who has both gravitas and charisma.”

Chris Gotwalt is the Director of Statistical Research and Development at JMP, a business division of SAS, and leads the statistical software development and testing teams. Since joining SAS as a software developer in 2003, Gotwalt has made numerous contributions to JMP, mostly in the area of numerical algorithms and in the creation of new statistical techniques. He developed many of the numerical algorithms that underlie the analytical tools within JMP, including those for linear mixed models, linear and nonlinear optimal designed experiments, neural networks, and reliability modelling.

All are welcome to this complimentary event, although registration in advance is essential due to limited space.

For more information and to reserve your place, please visit http://www.prismtc.co.uk/jmp