When I was in graduate school, one of my hobbies was to bake cookies for the department. For one of the basic chocolate chip cookie recipes, it wasn’t uncommon to switch the chocolate chips with another ingredient that was on sale that week (I was a grad student, after all).
In my previous blog entry, I discussed the purpose of the Alias Matrix in quantifying the potential bias in estimated effects due to the alias terms. In this blog post, we look at an example that creates a D-optimal design and an Alias Optimal design with the same number of
When I create a design, the first place I typically look to evaluate the design is the Color Map On Correlations. Hopefully, I see a lot of blue, implying orthogonality between different terms. The Color Map On Correlations contains both the model terms and alias terms. If you have taken
As we head into February, your 2014 goals are likely already made, and the work on meeting those goals has begun in earnest. For many scientists and experimenters, that means designing the first set of experiments for projects. Many times, those experiments will be screening experiments, experiments designed to identify
One of my favorite new features in JMP 11 design of experiments is the Fast Flexible Filling (FFF) design in the Space Filling Design platform. When the JMP 11 Previews were released, Brad Jones showed an example of using FFF designs to place air quality monitors over the state of
Last week, I wrote about the Custom Design user interface for power calculations that is new for JMP 11. My goal for this week’s blog post is to explain how to interpret the new power analysis for the two-level screening designs including screening with hard-to-change factors. What is so different
Last year, I wrote two blog posts about power analysis for designed experiments. Since then, JMP 11 was released, and the user interface for power analysis in the Custom Designer changed. This post introduces the new interface and shows how to use it profitably. Why did you change the interface?
JMP was delighted to welcome Peter Goos and Bradley Jones, two thought leaders in the area of design of experiments (DOE), to our Marlow office in the UK last week to talk about best practice in DOE. Box, Hunter and Hunter explained in their seminal text, Statistics for Experimenters, that
The JMP team held a seminar on Sept. 17 in France that focused on design of experiments. Bradley Jones and Peter Goos led this half-day event, and they covered various aspects of design of experiments using four different case studies. They introduced the definitive screening design, which is new in
Congratulations to Peter Goos and Bradley Jones for winning the 2012 Ziegel Prize for their book, Optimal Design of Experiments: A Case Study Approach. Jones, who is Principal Research Fellow at JMP and a world-renowned researcher in design of experiments, received the prize certificate (right) Tuesday at JSM 2013 in