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Fractional Designs & Other Screening Techniques

Fractional Designs & Other Screening Techniques

In preliminary research phases, the number of potentially influential factors to investigate is usually large. Screening designs are essential to identify the most influential factors with a reasonable number of runs in preliminary research phases.

Course Details

Learning Objectives

Learning Objectives:

Upon completion of this module, participants will be able to:

  • Understand the limitations of full factorial designs when the number of study factors is large
  • Choose an appropriate screening design given the study type and objective
  • Construct the selected screening design
  • Analyze the results of the experiment to determine which factors are influential
  • Interpret the results of screening designs
  • Know the advantage and drawbacks of several types of screening designs

Target Audience

Target Audience:

This module is primarily intended for people conducting preliminary experiments who wish to understand the impact of several factors on a given phenomenon. It is intended for anyone requiring efficient tools for selecting the most influential factors to study in later phases of the experimental process for optimization purposes.



Participants must have a working knowledge of the construction of general full factorial designs (main effects, interactions, etc.) and analysis of Variance (ANOVA), or, equivalently, must have attended the courses: 

Course Outline

Course Outline:
    • Strengths & Weaknesses of Full Factorial Designs
    • Principles of Fractional Designs "Screening Designs"
    • Reducing the Number of Runs Efficiently
    • The Notion of Modeling in Fractional Designs
    • Integrating the Study Objective into the Design
    • Impact of Fractioning on the Design
    • Construction of Screening Designs
    • Statistical Analysis of Screening Designs
    • Other Types of Screening Designs
    • Summary

Practical Info

Practical Info:


Recommended Duration: 1 day

Course Materials:

  • Course notes on statistical techniques
  • Sample datasets


    Related Sessions

    • Several experiments are conducted to determine whether differences exists between procedures, methods, treatments. Learn about the design and the analysis of simple comparative experiments and more complex situations.

    • Variation is present in every experiment. Learn about DOE techniques to control variation, and to maximise data quality. Commonly used experimental designs are discussed as well as the statistical data analysis tools.