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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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- Page 55 and 56: Where Did the Data in this Experime
- Page 57 and 58: Stepwise Fit Response: Shrinkage St
- Page 59 and 60: No-Confounding Design</stro
- Page 61 and 62: Hall II 15 Factor Design</s
- Page 63 and 64: Hall IV 15 Factor Design</s
- Page 65 and 66: Constructing the Recommended 6 Fact
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- Page 75 and 76: Alternatives to Resolution III <str
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- Page 83 and 84: Note that both main effects and two
- Page 85 and 86: Main effects are not aliased. One t
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- Page 89: A 12-Factor Example 1 1 1 1 1 1 1 1
- Page 92 and 93: The data for the example came from
- Page 94 and 95: Embarrassing Problem Case Suppose w
- Page 96 and 97: Reactor Case Study Box, Hunter and
- Page 98 and 99: Robust Screening Design</st
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- Page 102 and 103: The Case for Non-orthogonal <strong
- Page 106 and 107: Module 4 - Blocking • Many experi
- Page 108 and 109: Blocking • Blocking is a techniqu
- Page 110 and 111: The randomized complete block desig
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- Page 118 and 119: In general, if there are p treatmen
- Page 120 and 121: Back to tire testing • Suppose th
- Page 122 and 123: Module 4 - Summary • Most design
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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
- Page 144 and 145: CI on the mean response at a point
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- Page 149 and 150: Useful References on RSM • Box, G
- Page 151 and 152: Categorical and Continuous Variable
- Page 153 and 154: Goals Module 7 - RSM with Factor Co
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A problem with a constrained design
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JMP Default RSM Design</str
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Design Comparison
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Module 7 - Summary • Constraints
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Robust Parameter Design</st
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The Response Surface Approach Secti
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Filtration Robust Processing Exampl
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JMP Demo
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• Goals Module 9 Mixture
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Mixtures occur in lots of</
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Simplex Designs Si
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An experiment involving shampoo for
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Makeup of an Aircr
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Mixtures in JMP Ternary Plot .1 X1
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• Goals Module 10 - Covering Arra
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Covering Array Definition A coverin
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Covering arrays 1 1 1 1 1 2 2 2 2 2
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Covering arrays and sof</st
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Example - Air to ground missile sys
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CA(N:2,k,2) Results k 2-3 4 5-10 11
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References • R. Brownlie, J. Prow
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Module 10 - Summary • Covering ar
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199 What is a supersaturated design
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201 A more general definition… Su
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203 Classical “supersaturated”
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205 Case 2 - Fractional Factorial <
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207 Problem D-Optimal designs depen
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209 Example 2 6-2 Fractional Factor
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211 Bayesian D-Optimal designs Find
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213 Question Why should only higher
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Card Trick in JMP
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DOX Course - Final Thoughts 1. Opti