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Design of<
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What Is a Designed
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What Is a Response? A response is a
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What is a model? a simplified mathe
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Important Points from the Fathers <
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ANOVA Model for Mileage Study Note
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Orthogonal Coding and Orthogonal <s
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ANOVA/Regression Model - Matrix Not
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Categorical Factor Coding - 2 level
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Continuous Factor Coding MR - midra
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The Model/Design R
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The Model/Design R
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Design Optimality
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Simple experiment for three factors
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Standard designs using an optimal d
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INPUTS (Factors) Airspeed Turn Rate
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Fractional Factorial designs are D-
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Consider the 2 5-1 - Again Created
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JMP Demo Relative Variance
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INPUTS (Factors) 40 SPEAR AGM Tests
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Suppose that we want to focus on ma
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Alias Matrix Effect Intercept A B C
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Module 2 - Summary 1. Main message
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Regular Designs ma
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Define Nonisomorphic Two designs ar
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Screening for Shrinkage Contrasts T
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Where Did the Data in this Experime
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Stepwise Fit Response: Shrinkage St
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No-Confounding Design</stro
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Hall II 15 Factor Design</s
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Hall IV 15 Factor Design</s
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Constructing the Recommended 6 Fact
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Color Plot for the Standard Minimum
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Recommended Nonregular 7 Factor <st
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Color Plot for the Standard Minimum
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Recommended Nonregular 8 Factor <st
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Alternatives to Resolution III <str
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Recommended 10 Factor Desig
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Recommended 12 Factor Desig
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Recommended 14 Factor Desig
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Note that both main effects and two
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Main effects are not aliased. One t
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Plackett-Burman Design</str
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A 12-Factor Example 1 1 1 1 1 1 1 1
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The data for the example came from
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Embarrassing Problem Case Suppose w
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Reactor Case Study Box, Hunter and
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Robust Screening Design</st
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Robust Screening Design</st
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The Case for Non-orthogonal <strong
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References Hall, M. Jr. (1961). Had
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Module 4 - Blocking • Many experi
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Blocking • Blocking is a techniqu
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The randomized complete block desig
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Cars The Latin Square Desig
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JMP Demo
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Another Example of
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- Page 120 and 121: Back to tire testing • Suppose th
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- Page 124 and 125: Split-plot Graphic Definition
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- Page 128 and 129: General procedure Split-plot <stron
- Page 130 and 131: Scenario 1. Four factors Split-Plot
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- Page 136 and 137: OLS vs GLS Data Analysis OLS Analys
- Page 138 and 139: Module 6 - Introduction to RSM •
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- Page 142 and 143: Response Surface Methodology • Wh
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- Page 149 and 150: Useful References on RSM • Box, G
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- Page 153 and 154: Goals Module 7 - RSM with Factor Co
- Page 155 and 156: A problem with a constrained design
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- Page 159 and 160: Design Comparison
- Page 161 and 162: Module 7 - Summary • Constraints
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- Page 165 and 166: The Response Surface Approach Secti
- Page 167: Filtration Robust Processing Exampl
- Page 171 and 172: • Goals Module 9 Mixture
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- Page 183 and 184: • Goals Module 10 - Covering Arra
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- Page 187 and 188: Covering arrays 1 1 1 1 1 2 2 2 2 2
- Page 189 and 190: Covering arrays and sof</st
- Page 191 and 192: Example - Air to ground missile sys
- Page 193 and 194: CA(N:2,k,2) Results k 2-3 4 5-10 11
- Page 195 and 196: References • R. Brownlie, J. Prow
- Page 197 and 198: Module 10 - Summary • Covering ar
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- Page 203 and 204: 203 Classical “supersaturated”
- Page 205 and 206: 205 Case 2 - Fractional Factorial <
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- Page 209 and 210: 209 Example 2 6-2 Fractional Factor
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- Page 215 and 216: Card Trick in JMP
- Page 217: DOX Course - Final Thoughts 1. Opti