# Multivariate Data Analysis - Level 1

December 31-30, 1969 | ,

### Course Overview

Find out how to make breakthrough improvements using powerful design of experiments (DOE) techniques. Start with our Experiment Design Made Easy workshop to learn about using factorial designs for finding which factors you need to focus on. Discover previously unknown interactions that often prove to be the key to success. Learn how to use powerful ANOVA analysis methods that give you confidence in your findings.

### Who should participate in this program?

Experiment Design Made Easy covers the practical aspects of DOE. (Students may purchase the optional "DOE Simplified" book for reference.) You learn all about simple but powerful two-level factorial designs. During this introductory DOE workshop, you will discover how to effectively:

• Understand the motivation for factorial designs
• Implement the DOE planning process
• Interpret analysis of variance (ANOVA)
• Discover hidden interactions
• Capitalize on efficient fractional designs for screening or characterization
• Use power to properly size designs
• Determine when to use transformations
• Explore multilevel categoric factors
• Set up split-plot designs
• Follow the strategy of experimentation from screening to response surface methods

### Course Details

#### Day 1

• Section 1—Introduction to Factorial Design
• Background and motivation for factorial designs
• Factorial design planning process
• Basics of factorial design: Case study
• Selecting effects - Half-normal plot and Pareto chart
• ANOVA and residual diagnostics
• Main effects, interaction, contour and 3D surface plots
• Into to multiple-response optimization

#### Lunch

• Section 2—Enhancements for Full Factorials
• Replicated 23 full factorial: Case study
• Explanation of powe
• 24 full factorial exercise
• Section 3—Blocking and Fractionating Factorials
• How to set up optimal blocking: Case study
• Factors interacting vs three-factor interactions (3FIs)e
• How to set up fractional factorials
• Understanding aliases
• Homework
• 25-1 fractional factorial exercise

#### Day 2

• Section 4—Transformations
• Dangers of deleting outliers: Case study
• How to use transformations – details
• Reinforce transformation concepts: Exercise
• Minimum-run characterization (MR5) design: Exercise
• Dealing with a low-power response
• Summary of transformations
• Section 5—Multilevel Categoric Design (General Factorial)
• Multilevel categoric design with replication: Case study
• Fractionating via optimal (custom) design: Case study
• Intro to optimal (custom) design
• Model graphs for multilevel categoric designs

#### Lunch

• Section 6—Split-Plot Designs
• Restriction randomization
• Split-plot design: Case study
• Section 7—Strategy of Experimentation
• DOE Experimentation cycle: Case study
• Screening in the presence of two-factor interactions (2FIs)
• Minimum-run screening (MR4) designs
• Transition to characterization design
• Augmentation to response surface method (RSM) design
• Central composite design
• Optimization and confirmation runs
• Screening designs summary
• Section 8—Overview and Homework
• Recommendations for choosing a factorial design
• Mixture design overview and case study
• Homework review (breakout session, if time allows)
• Conclusion and resources

### General Terms

The course fees includes lunch, tea / coffee, course material and 30-days trial installation of The Unscrambler. Participants are required to bring their own Laptop, organize transport to / from training venue and accommodation at their own cost. Deadline for registrations: 2 weeks before the course start.

Payments: 30 days net from date of invoice.

Cancellation: Cancellations up to 1 week prior the course start date, will be refunded with 50% of the registration fee, after this limit will not be refunded.

Substitution: The course participants may be substituted or join a later training provided that CAMO is notified.

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