JMP
www.jmp.com
SAS created JMP in 1989 to empower scientists and engineers to explore data visually. Since then, JMP has grown from a single product into a family of statistical discovery tools, each one tailored to meet specific needs. All of our software is visual, interactive, comprehensive and extensible.
JMP is the data analysis tool of choice for hundreds of thousands of scientists, engineers and other data explorers worldwide. Users leverage powerful statistical and analytic capabilities in JMP to discover the unexpected.
Contact info
- Tel:
- +44 1628 490 974
- Email:
- jmpuk@jmp.com
WebinarBuilding organisational consensus around the tools of digital chemistry
Learn how change agents at Johnson Matthey developed a coalition of support for data-driven science
- Sponsored
Digitalisation is the future of science, just ask a biologist
Biology has some life lessons for chemistry
- Webinar
Workshop: Getting started with Design of Experiments
Join JMP experts for this three-part workshop and learn how to use experimentation more efficiently and achieve better outcomes faster
- Sponsored
You don’t need coding to be a chemist
Writing your own software can be useful, but what matters is knowing how to use it
- Webinar
Nobel prize in chemistry: reactions
See our reaction to the 2022 Nobel prize in chemistry announcement
- Webinar
Make better data-based decisions with statistical modelling techniques
Join JMP experts for this three-part workshop and make better decisions with your data using statistical modelling
- Webinar
Applications of modern Design of Experiments (DoE)
Join JMP experts for this three-part workshop and improve your experimentation
- Webinar
Speed up process development by making more from your offline and online data
Learn how the biotechnology R&D team at Clariant uses statistical modelling techniques to speed up the process development of their bio-ethanol product
- Webinar
Double your impact by getting started with Design of Experiments (DoE)
Join JMP experts for this three-part workshop and improve your experimentation
- Webinar
Smarter experimentation for engineers and scientists
Join us 1-5 November for your last chance to get involved with this innovative online training programme in design of experiments
- Webinar
Unlock the potential of definitive screening designs to drive your projects forward
In this webinar we help demystify DSDs and reveal how their complexity can be harnessed for manufacturing processes
- Webinar
Find robust operating points using JMP’s Simulation Experiment tool
Learn how simulations can be used to minimise defect rate and improve crucial targets
- Webinar
The era of data analytics: What it takes to succeed beyond the hype
Find out how to make better decisions about your data using analytics and subject matter knowledge
- Webinar
The age of digital chemistry
Join us to learn how data can solve existing bottlenecks in synthetic chemistry and why data analysis demands a multidisciplinary approach
- Webinar
A recipe for success in exploiting machine learning and data science
Join us to discover how data science and big data are revolutionising decision making – and why claims that experts are no longer needed are misleading
- Webinar
Statistics versus machine learning: should we all learn artificial intelligence?
Join us to understand the limitations of deep learning & why advanced statistical modelling is still needed – both in academic curricula and in the toolbox of any scientist or engineer
- Webinar
Gaining an edge through smarter experimentation
Learn how to double your R&D capacity and get more products to market in less time – and at a lower cost
- Webinar
Good practices in data analytics
Join us to learn how the University of Limerick develops skills and knowledge of data analytics via their Pharmaceutical Manufacturing Technology Centre (PMTC)
- Webinar
Smarter experimentation for scientists and engineers
An innovative online training programme in design of experiments
- Webinar
Scaling up processes with Design of Experiments
Learn how Fujifilm Diosynth Biotechnologies uses Design of Experiments to understand the best way to scale up reactions
