The Advanced Design of Experiments program focuses on increasing the participant's ability to formulate and solve real problems.

It also promotes decision making in the different areas of application through the correct choice of the statistical method and the most appropriate optimization algorithm in each case.


The PXS Advanced DOE program participant will be able to formulate, analyze and validate complex statistical models applicable to practical problems, which allows effective problem solving in their company.

You will also be able to discuss the validity, scope and relevance of the proposed solutions.


Quality engineers, quality supervisors, quality managers, quality managers, continuous improvement engineers, validation engineers, production supervisors, production managers, production managers, product design engineers, manufacturing engineers.

  • Multiple Regression.
  • Best subsets method.
  • “Stepwise”
  • Rpres-Rsq (adj.).
  • Collinearity.
  • Response surface.
  • Central compound designs.
  • Box-Behnken.
  • Optimization of Multiple Responses.
  • Calculations for more marked ascent.
  • Overlaid contour plots.
  • Unbalanced experiments.
  • Taguchi Designs.
  • Static Design.
  • Dynamic Design.
  • Prediction.
  • Nested Layouts.
  • Split Plot Designs.
  • Design of Experiments with attributes:
  • Binary Logistic Regression.
  • Ordinal Logistic Regression.
  • Nominal Logistic Regression.
  • Freeman Tukey Transformations.
  • Design with Mixtures:
    • Simplex reticular design.
    • Centroid.
    • Pseudocomponents.
    • Restrictions.
    • Trace charts.
    • Mixing with process variables.

This course grants 4.00 recertifiable units (RU's) applicable to recertifications in CSSBB, CQE and CRE of the ASQ