JMP - Modern Screening Designs Training Course and Workshop in Bangalore, Mysore, Chennai, Hyderabad, Pune, Mumbai, Delhi, Noida, Gurgaon, Kolkata

This JMP - Modern Screening Designs training course presents strategies and methods for designing experiments to screen many factors in an optimal study, as well as several specialized analytical tools that respect the limited information available in such experiments. This course is designed to help scientists and engineers choose an appropriate technique for their particular situation.

By attending JMP - Modern Screening Designs workshop, delegates will learn to:

Recognize situations that benefit from a screening experiment
Make a fractional factorial design or plackett-burman design
Make an orthogonal or near-orthogonal array or a definitive screening design
Make a bayesian d-optimal design or split-plot design with custom design
Identify situations where each of the screening designs might be most useful
Identify likely effects in the response using the effect screening emphasis and tools in the fit least squares platform or the screening platform
Select a model using the stepwise platform with forward selection or all possible models under the heredity restriction.

Attend a training on JMP - Custom Design of Experiments or JMP - Classic Design of Experiments or have equivalent experience.

The JMP - Modern Screening Designs class is ideal for:

Advanced JMP analysts who need to screen many factors through experimentation

Need for screening

Learning the important principles in screening such as: the impact that choice of design has on the variance of estimates and bias in model prediction, inflation of variance in parameter estimates due to correlation, and estimation efficiency as measured by the estimate's confidence interval size
Planning experiments with classic screening solutions including fractional factorial and plackett-burman designs

Combinatorial screening designs

Planning experiments with orthogonal or near-orthogonal arrays
Planning experiments with definitive screening designs
Planning experiments with custom designs, like bayesian d-optimal designs and split-plot structures for restricted randomization

Model selection in screening

Identifying active factors using the effect screening tools in the fit least squares platform
Selecting models with the screening platform
Selecting models with forward step-wise regression
Selecting models with all-subsets with heredity restrictions

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JMP - Modern Screening Designs

COURSE AGENDA

Need for screening

Combinatorial screening designs

Model selection in screening

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