Experiment Design Made Easy

San Diego, CA
Jan. 28, 2020 - Jan. 29, 2020

Early Bird deadline Dec 17, 2019. This class is selling out quickly - a few spots remain!

 


In this 2-day hands-on workshop participants set up, analyze, and interpret two-level factorial, general factorial and fractional factorial designs. Learn how to identify the vital few effects and discover unknown interactions through the use of powerful design of experiment (DOE) techniques. Master the user-friendly Design-Expert® software.

NOTE: This class focuses on factorial and fractional-factorial designs for super-efficient detection of factor effects and process characterization. It is a subset of the full 3-day Modern DOE for Process Optimization workshop, which adds response surface methodology for complete process optimization.

A 10% discounted Early Bird rate applies to registrations made 6 weeks prior to the workshop date. A $200/person discount is applied for 2 or more attendees registering together. Price includes a $95 fee for workshop materials which is subject to state and local taxes.

Books, software and consulting are discounted 20% when purchased with a workshop.

Recommended items

DOE Simplified: Practical Tools for Effective Experimentation, 3rd Edition

In DOE Simplified, 3rd Edition—a comprehensive introductory text geared towards experimenters with minimal statistical background—the authors take a fresh and lively approach to learning the fundamentals of factorial experiment design and analysis.

This book is currently out of stock. Please order from your preferred book vendor. Ebook editions are available.

Design-Expert® Software Subscription

Make breakthrough improvements to your product and process with Design-Expert software. Screen for vital factors and components, characterize interactions and, ultimately, achieve optimal process settings and product recipes.

 

Consulting - Hourly

Purchase consulting services from our design of experiments (DOE) experts in 1-hour increments. We can provide advice on building your design or helping to analyze your data.

 

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