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Why Design Experiments? The complete 7-part blog series.

Design of Experiments (DoE) is one of the most important data science tools for scientists and engineers.


I set out to write a series of blog posts to demystify DoE with simple explanations of some of the terms and concepts that can be confusing for people when they are starting out. Click here for links to all 7 posts in the series. I recommend you start with reason #1.




I discussed each of the blog posts in a series of JMP On Air segments: Reason 1 , Reason 2 , Reason 3 , Reason 4 , Reason 5 , Reasons 6 and 7.


For anyone that wants to look at how the experiment was designed and play with the actual data that was collected (again, thanks to Camilla and Jonathan at Anatune) I have attached jmp data tables.

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Level III

Thanks a lot 


No problem. Let me know if you have any questions and also what you learn from looking at the data.

Level III

Of course I ' ll do.

Level IV

@phil_kay  thanks for your contribution here and for bringing this to life on Introducing JMP ON Air .

I've been slowly making my way through the material and I am enjoying it very much.


One thing I was wondering, if it would be possible for you to provide the table of the 4,374 runs? I want to practice making that factor plot that you made in graph builder, so that I can appreciate more the complexity of the full factorial design versus the geometrically reduced factor space offered by the DSD design.


graph builder cell plot.png


Thanks for your kind feedback, @PatrickGiuliano. I have attached the 4374-run full factorial. The table includes simulated results and scripts for various visuals and analyses. I hope they are helpful. Please let me know if I can do anything else to help.

Level IV

Awesome thanks @phil_kay! I'll take a look and let you know if I have any questions.  Cheers @PatrickGiuliano