1. The Essentials of 2-Level Design of Experiments Part I: The Essentials of Full Factorial Designs
Developed by Don Edwards, John Grego and James Lynch Center for Reliability and Quality Sciences Department of Statistics University of South Carolina

2. Part I.3 The Essentials of 2-Cubed Designs
Methodology
Cube Plots
Estimating Main Effects
Estimating Interactions (Interaction Tables and Graphs)
Statistical Significance (Effects Probability Plots)
Example With Interactions
A U-Do-It Case Study
Computer help to come

3. 23 Means What? Methodology 23 Designs
3 Factors (Usually Labeled A, B, C)
2 Levels Lo (-) and Hi (+)
Comparing 8= 23 Recipes

4. Methodology 23 Designs - TV with Three Adjustment Knobs
The picture is the Lo Lo Hi response. Lo and Hi are factor settings
Knob Setting Is At The Top

5. Methodology Tabular and Graphical Methodology
Cube Plots To See Relationships Between The Response and Factor Effects
Sign Tables To Estimate Factor Effects
Probability Plots To Determine Statistically Significant Factor Effects
Interaction Graphs and Tables To Interpret Interactions
ANOVA Tables

6. Methodology Cube Plot Template

7. Methodology Cube Plot
Note How The Responses are Entered into the Cube (Lo = - and Hi =+)
Y(i) will be replaced with, e.g., Y(---) or Y(111).

8. Methodology Cube Plot (OVAT)
Note How The Responses are Entered into the Cube (Lo = - and Hi =+)
Y1 is the Response when all the Factors are Lo (- - -)
Y2 corresponds to (+ - -), Y3 to (- + -) and Y5 to (- - +)
Factor settings for OVAT design

9. Methodology Cube Plot (Full Factorial)
Note How The Responses are Entered into the Cube (Lo = - and Hi =+)
Y8 is the Response when all the Factors are Hi (+ + +)
Y4 corresponds to (+ + -), Y6 to (+ - +) and Y7 to (- + +)
Factor settings for full factorial design

10. Methodology Example 1: Targeting a Process/Reducing Variation

11. Methodology Example 1 - Accuracy versus Precision
Skip

12. Methodology Example 1 - Improving a Process
Which Factors Affect
Accuracy?
Precision?
Skip. Slightly different picture from I.2 and I.5, but same factor effects

13. Statistical Engineering Economic
Methodology Example 1 - Targeting a Process/Reducing Variation Various Types of Significance
Statistical
Engineering
Economic
Statistical significance may not lead to a practical difference
Ted Shropshire at Becton-Dickinson often found statistical significance, but economics didn’t work out.
-Sara Lee Study
-No Statistical Significance Difference Between Needles
-But This Was Economically Significant