Learn modern experimental strategy, including factorial and fractional factorial experimental designs, designs for screening many factors, designs for optimization experiments, and designs for complex experiments such as those with hard-to-change factors and unusual responses. There is thorough coverage of modern data analysis techniques for experimental design, including software. Applications include electronics and semiconductors, automotive and aerospace, chemical and process industries, pharmaceutical and bio-pharm, medical devices, and many others.
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Learn modern experimental strategy, including factorial and fractional factorial experimental designs, designs for screening many factors, designs for optimization experiments, and designs for complex experiments such as those with hard-to-change factors and unusual responses. There is thorough coverage of modern data analysis techniques for experimental design, including software. Applications include electronics and semiconductors, automotive and aerospace, chemical and process industries, pharmaceutical and bio-pharm, medical devices, and many others.
Learn modern experimental strategy, including factorial and fractional factorial experimental designs, designs for screening many factors, designs for optimization experiments, and designs for complex experiments such as those with hard-to-change factors and unusual responses. There is thorough coverage of modern data analysis techniques for experimental design, including software. Applications include electronics and semiconductors, automotive and aerospace, chemical and process industries, pharmaceutical and bio-pharm, medical devices, and many others.
You can see an overview of the specialization from Dr. Montgomery here.
What's inside
Four courses
Experimental Design Basics
(0 hours)
Experimental Design Basics
(0 hours)
Factorial and Fractional Factorial Designs
(0 hours)
Factorial and Fractional Factorial Designs
(0 hours)
Response Surfaces, Mixtures, and Model Building
(0 hours)
Response Surfaces, Mixtures, and Model Building
(0 hours)
Random Models, Nested and Split-plot Designs
(0 hours)
Random Models, Nested and Split-plot Designs
(0 hours)Learning objectives
- Plan, design and conduct experiments efficiently and effectively, and analyze the resulting data to obtain valid objective conclusions.
- Use response surface methods for system optimization as a follow-up to successful screening.
- Use experimental design tools for computer experiments, both deterministic and stochastic computer models.
- Use software tools to create custom designs based on optimal design methodology for situations where standard designs are not easily applicable.
- Plan, design and conduct experiments efficiently and effectively, and analyze the resulting data to obtain valid objective conclusions.
- Use response surface methods for system optimization as a follow-up to successful screening.
- Use experimental design tools for computer experiments, both deterministic and stochastic computer models.
- Use software tools to create custom designs based on optimal design methodology for situations where standard designs are not easily applicable.
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