This course offers a fresh perspective about designing experiments through state-of-the-art features in JMP. This course specifically focuses on the principles of designing an experiment and how to use all of them to achieve an optimal design.

Learn how to

• use custom design for any experiment
• choose appropriate criteria for optimal design
• effectively and efficiently test factor effects or predict responses
• augment existing experiments to address new questions
• design and analyze experiments with hard-to-change factors
• eliminate noise from nuisance factors
• find best factor settings to achieve desired response levels.

Who should attend

Directors, managers, engineers, scientists, technicians, and analysts who work in discovery, research, development, and quality assurance or control, as well as Black Belts who are working on Six Sigma projects

Formats available	Standard Duration
Classroom:	2.0 days
Live Web Classroom:	4 half-day session(s)	System Requirements
e-Learning:	14 hours/180 day license	System Requirements

Before attending this course, you should complete the JMP Software: A Case Study Approach to Data Exploration and JMP Software: Statistical Decisions Using ANOVA and Regression courses or have equivalent experience.

This course addresses JMP software.

Introduction

• introduction to design of experiments
• introduction to custom design
• about responses

Experiments with One Factor

• testing a categorical factor
• testing a continuous factor
• validating the model
• testing a quadratic effect

Experiments with Two Factors

• testing two categorical factors
• testing one continuous factor and one categorical factor
• testing with one blocking factor
• testing two continuous factors

Experiments with Multiple Factors

• two responses to five factors
• three responses to seven factors