In Person

Experimental Design for Productivity and Quality in Research & Development

Improve your R&D quality and efficiency. Match appropriate experimental designs to real-world problems.

About the Course

Youtube ID: Ul2zmoUHnh8

Two expert instructors show you how to significantly improve your R&D quality and efficiency and how to match appropriate experimental designs to real-world problems.

The course covers:

  • Basic concepts of experimental design
  • Strengths and limitations of popular experimental design techniques
  • Applicability of common designs
  • Determination of which experimental designs are appropriate for particular situations

What You Will Learn

  • Get solutions to your experimental design problems from seasoned experts.
  • Learn how to significantly improve R&D quality and efficiency.
  • Make your experiments more efficient by saving resources and eliminating unnecessary experimentation.
  • Learn how to match appropriate experimental designs to real-world problems.
  • Gain an improved understanding of statistical process control and statistical quality control.
  • Understand statistical terminology and communicate more easily with statisticians.
  • Develop a foundational understanding of advanced design techniques.
  • Receive a brief introduction to Taguchi methods.
  • Learn about commercial software packages for data treatment.
  • Improve your skills in communicating research strategies to co-workers.

Who Should Attend

Chemical scientists, engineers, R&D managers, and others who need to learn proven methods for designing quality into products and processes.

The course assumes no previous knowledge of statistics and is aimed at both beginning and experienced R&D workers.

Course Outline

  • Day 1

    • Linear Models
    • The importance of n, p, and f<
    • Regression Analysis
    • Residuals
    • Degrees of Freedom
    • Basic Design Concepts
    • Looking for Pure Error
    • Calibration
    • Coding
    • Factorial-Type Designs
    • Yates Algorithm
    • Screening Designs
  • Day 2

    • Plackett-Burman Designs
    • Hadamard Designs
    • Taguchi Designs
    • Response Surface Designs
    • Central Composite Designs
    • Box-Behnken Designs
    • Mixture Designs
    • Comparing Different Designs
    • Choice of Model
    • Matrix Least Squares Solution
    • Replication and Pure Error
    • Sums of Squares
  • Day 3

    • The Rosetta Stone of Statistics
    • Looking for Lack of Fit
    • Orthogonal Designs
    • Classical Data Analysis
    • Fractional Factorial Designs
    • Blocking
    • Multiple Response
    • Scheffe Mixture Model
    • Intercept Mixture Model
    • Analysis of Variance (ANOVA)
    • Correlation Coefficient
    • Confidence Intervals and Bands

Dates, Locations, and Prices

Five for four! Register five people for one course, one person for five courses, or any combination in between and your fifth registration is free. The free registration will be the course of the lowest price. Please note: This discount cannot be combined with any other discount offered. 

About the Instructor(s)

Stanley N. Deming

President, Statistical Designs

Stanley Deming is Professor Emeritus at the University of Houston, Texas. He is President of Statistical Designs, through which he offers consulting in experimental design, optimization, and statistical analysis.

Stephen L. Morgan

Professor, University of South Carolina

Stephen L. Morgan is a Professor of Chemistry at the University of South Carolina. His research involves chemometrics and statistics, forensic analytical chemistry, spectroscopy and separations.