The Stat-Ease development team ushers in a new era with the newest version of Design-Expert (DX) and Stat-Ease 360 (SE360) software: the beginning of time-based releases per the “release early, release often” approach of the modern software industry. This first release (v22.0) features:

• Analysis Summary: expands the previous “Coefficients Table” with more model-fit statistics. Easily view p-values, R-squares, model equations and more, across all responses.
• Custom Graphs: node provides greatly expanded capability to the prior “Graph Columns.” You can now plot analysis data like predicted values and residuals—plus distinguish points by size and symbol.
• Shaded Intervals: Prediction, confidence, and tolerance intervals can now be set to “shaded” to color the bands, thus creating a far better view of the uncertainty around the fitted response.

• Hosted License Option: Run your software on multiple devices without requiring an on-premises license server, thus reducing costs for DIY software deployment and management.
• Direct Excel Import/Export (SE360 Exclusive): Avoid the hassle of copy and paste!  
• Random Blocks (SE360 Exclusive): Blocks can now be treated as a random input. This facilitates precise statistical analyses for uncontrolled variables such as the day-by-day differences blocked out in this demonstration.

These are only a few of the many niceties provided in this latest iteration of DX/SE360. Contact our Sales team now to purchase a license or lay out the path for an upgrade to these leading-edge statistical tools developed by the world-class team of Stat-Ease programmers, statisticians, and engineers.

Can factorial models be extrapolated?

Original question from a Researcher | Chemical R&D:
“We have recently purchased a Stat-Ease software license and need some help getting started. An Excel file with the relevant data is attached.”

Answer:
OK, I used the handy Import function to bring in this 2³ factorial design with 2 center points. For maximum flexibility, the import feature applies polynomial models—apropos for response surface methods (RSM) but not two-level factorials.* I worked around that via Advanced Options on the Configure tab for each response—making them Factorial for modeling, thus taking advantage of DX's specialized tools for these designs. Then I analyzed each response. The first one, Yield, was most interesting—its Diagnostics indicating via the Box-Cox plot that an inverse square root transformation enhances the fit.

PS It is great you did center points for this characterization design, but next time do 3 or 4 to provide more power for the curvature test.

*(The Import tool assumes that data coming in stems from non-designed experiments that typically feature three or more levels for each factor, as discussed in my webinar on Evaluating and Exploiting Existing Data.)

Follow-up question:

• 8 décembre de 14h à 15h (CET) — Introduction aux Plans d'Experiences (DoE) sera présenté en français par Alice Croguennoc
• January 11—The Art of Augmentation – Adding Runs to Existing Designs by Shari Kraber
• January 18—A Crash Course in Mixture Design of Experiments by Martin Bezener

See this web page for the complete schedule of upcoming Stat-Ease courses. To enroll in the workshop that suits you best, click Register on that webpage, or click here to contact us.
 

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