This course teaches you how to design and analyze experiments in JMP to find the vital few factors or optimize the process response. The course emphasizes the principles of experimental design while demonstrating classic approaches to screening designs and response surface designs.

Learn how to

• explain the fundamental principles of designed experiments
• generate and analyze full and fractional factorial designs
• generate and analyze classic response surface designs
• generate and analyze blocked and split-plot designs
• generate custom designs and augment existing designs.

Who should attend

Anyone who would like to understand and improve products and processes, such as engineers, scientists, and Six Sigma practitioners

Formats available	Standard Duration
e-Learning:	16 hours/180 day license	System Requirements

Before attending this course, it is recommended you

• complete the JMP® Software: A Case Study Approach to Data Exploration course or have equivalent experience
• complete the JMP® Software: Statistical Decisions Using ANOVA and Regression course or have equivalent experience
• have some knowledge of the basic tenets of design of experiments.

Introduction to Design of Experiments

• review of basic statistical concepts
• introduction to experimental design
• completely randomized designs

Multiple Factor Designs

• full factorial designs
• 2^k factorial designs
• fractional factorial designs

Response Surface Methodology

• concepts and terms
• classic response surface designs

Blocked and Split-Plot Designs

• randomized complete block designs
• randomized incomplete block designs
• split-plot designs

Introduction to Custom Design

• custom design generation
• optimal augmentation