This complimentary workshop is offered to all teachers, researchers and students at Imperial College London who want to learn more about design of experiments (DOE) and data analysis. DOE skills are highly demanded by industry and still under-represented in many university curricula.
Design of experiments is a practical and ubiquitous approach for exploring multifactor opportunity spaces, and JMP offers world-class capabilities for design and analysis in a form you can easily use without any programming. To properly uncover how inputs (factors) jointly affect the outputs (responses), DOE is the most efficient and effective way – and the only predictable way – of learning. Unlike the analysis of existing data, designed experiments can tell you about cause and effect, drive innovation and test opportunities by exploring new factor spaces.
In addition to classical DOE designs, JMP also offers an innovative custom design capability that tailors your design to answer specific questions without wasting precious resources. Once the data has been collected, JMP streamlines the analysis and model building so you can easily see the pattern of response, identify active factors and optimize responses.
In this course you will learn to:
- understand why we use DOE
- analyze experiments with a single categorical factor using analysis of variance (ANOVA)
- analyze experiments with a single continuous factor using regression analysis
- understand the difference between classical and optimal designs
- design, analyze and interpret screening experiments incl. Definitive Screening Design
- design, analyze and interpret experiments in response surface methodology
- augment designs for sequential experimentation
- apply robust optimization
- evaluate and compare designs
- understand advanced features like blocking, split-plot experiments and covariates
This format of this course will be a mix of concept presentations, live demos and hands-on exercises. The examples will focus on chemistry and biostatistics, but can be easily transferred to other fields like materials science, agri-food science or engineering.
Attendees should have access to JMP Pro (pre-installed). JMP Pro 15 is available for all attendees from Imperial College campuswide for both Windows and Mac, external attendees can use the JMP 15 trial. No prior knowledge required. All contents and demos will be shared with the participants.
Register for this Workshop on Eventbrite
Additional Resources:
- DOE applications in JMP
- Innovation in the Chemical Industry With Statistics and DOE, Interview with Kevin White, Applied Statistics Group Leader at Eastman
- The Integration of Big Data Analytics into a More Holistic Approach, a JMP White Paper By Roger W. Hoerl
Logistical Information:
- The workshop will be held at the Imperial College White City Campus (nearest Underground stations are White City and Wood Lane)
- Attendance at both days is required
- Sessions will run from 0930 to 1700 with breaks for morning tea, lunch and afternoon tea on both days
Tea and coffee will be provided but you must provide your own lunch (there are food outlets nearby)