Multiple Regression Analysis Example: Process Validation

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Multiple regression analysis example in the PDF link below addresses how to validate a multiple regression analysis.

My response to a posting at the Quality Digest’s, where I was the Six Sigma Discussion Forum Moderator.

Question: Multiple Regression Analysis

Once I’ve calculated my equation for multiple regression, how do I go about validation? My only direction, for now, is to take the residuals of the calculated vs. actual and create a control chart. Test an appropriate sample size again and calculate those residuals (actual vs. calculated). If they fall within the original control chart, the equation is considered valid. Does this seem correct? Any other suggestions?

Response: Multiple Regression Analysis

One approach that builds upon the described basic multiple regression model validation approach is:

  1. Use historical data to determine a multiple regression equation. A best subsets approach can be very useful to determine the key process input variables (KPIVs) to include within the equation.
  2. Create an infrequent subgrouping/sampling plan such that normal variation levels of the KPIVs will impact the XmR response control chart as common cause variability.
  3. … (download PDF for this and the other listed items)

Integrated Enterprise Excellence: Multiple Regression Analysis and More

Integrated Enterprise Excellence (IEE) Business Management System addresses the scorecard, analysis,and business improvement issues described in a 1-minute video


multiple regression analysis video


Multiple regression and other statistical tool usage for the IEE business management system and lean Six Sigma DMAIC process improvement roadmap is described in a 5 book series


Lean Six Sigma 2.0 Black Belt Free Training Material and Guide


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