Design of Experiments with MINITAB

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Overview

Most of the classic DOE books were written before DOE software was generally available, so the technical level that they assumed was that of the engineer or scientist who had to write his or her own analysis software. In this practical introduction to DOE, guided by the capabilities of the common software packages, Paul Mathews presents the basic types and methods of designed experiments appropriate for engineers, scientists, quality engineers, and Six Sigma Black Belts and Master Black Belts. Although instructions in the use of MINITAB are detailed enough to provide effective guidance to a new MINITAB user, the book is still general enough to be very helpful to users of other DOE software packages.

Every chapter contains many examples with detailed solutions including extensive output from MINITAB.

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Product Details

  • ISBN-13: 9780873896375
  • Publisher: ASQ Quality Press
  • Publication date: 10/31/2004
  • Pages: 520
  • Sales rank: 1,044,448
  • Product dimensions: 7.02 (w) x 10.28 (h) x 1.42 (d)

Table of Contents

Preface xiii
Acknowledgments xix
Chapter 1 Graphical Presentation of Data 1
1.1 Introduction 1
1.2 Types of Data 1
1.3 Bar Charts 2
1.4 Histograms 3
1.5 Dotplots 4
1.6 Stem-and-Leaf Plots 4
1.7 Box-and-Whisker Plots 5
1.8 Scatter Plots 6
1.9 Multi-Vari Charts 7
1.10 An Introduction to MINITAB 9
Chapter 2 Descriptive Statistics 19
2.1 Introduction 19
2.2 Selection of Samples 19
2.3 Measures of Location 20
2.4 Measures of Variation 21
2.5 The Normal Distribution 26
2.6 Counting 30
2.7 MINITAB Commands to Calculate Descriptive Statistics 34
Chapter 3 Inferential Statistics 37
3.1 Introduction 37
3.2 The Distribution of Sample Means ([sigma] Known) 38
3.3 Confidence Interval for the Population Mean ([sigma] Known) 41
3.4 Hypothesis Test for One Sample Mean ([sigma] Known) 42
3.5 The Distribution of Sample Means ([sigma] Unknown) 52
3.6 Hypothesis Tests for Two Means 56
3.7 Inferences About One Variance (Optional) 61
3.8 Hypothesis Tests for Two Sample Variances 65
3.9 Quick Tests for the Two-Sample Location Problem 68
3.10 General Procedure for Hypothesis Testing 73
3.11 Testing for Normality 75
3.12 Hypothesis Tests and Confidence Intervals with MINITAB 79
3.13 Sample-Size Calculations 82
Chapter 4 DOE Language and Concepts 93
4.1 Introduction 93
4.2 Design of Experiments: Definition, Scope, and Motivation 93
4.3 Experiment Defined 94
4.4 Identification of Variables and Responses 94
4.5 Types of Variables 96
4.6 Types of Responses 97
4.7 Interactions 98
4.8 Types of Experiments 99
4.9 Types of Models 100
4.10 Selection of Variable Levels 105
4.11 Nested Variables 106
4.12 Covariates 107
4.13 Definition of Design in Design of Experiments 107
4.14 Types of Designs 108
4.15 Randomization 109
4.16 Replication and Repetition 113
4.17 Blocking 114
4.18 Confounding 117
4.19 Occam's Razor and Effect Heredity 118
4.20 Data Integrity and Ethics 119
4.21 General Procedure for Experimentation 120
4.22 Experiment Documentation 136
4.23 Why Experiments Go Bad 139
Chapter 5 Experiments for One-Way Classifications 143
5.1 Introduction 143
5.2 Analysis by Comparison of All Possible Pairs Means 144
5.3 The Graphical Approach to ANOVA 145
5.4 Introduction to ANOVA 147
5.5 The Sum of Squares Approach to ANOVA Calculations 155
5.6 The Calculating Forms for the Sums of Squares 159
5.7 ANOVA for Unbalanced Experiments 160
5.8 After ANOVA: Comparing the Treatment Means 161
5.9 ANOVA with MINITAB 167
5.10 The Completely Randomized Design 172
5.11 Analysis of Means 176
5.12 Response Transformations 177
5.13 Sample Size for One-Way ANOVA 185
5.14 Design Considerations for One-Way Classification Experiments 188
Chapter 6 Experiments for Multi-Way Classifications 191
6.1 Introduction 191
6.2 Rationale for the Two-Way ANOVA 192
6.3 The Sums of Squares Approach for Two-Way ANOVA (One Replicate) 202
6.4 Interactions 203
6.5 Interpretation of Two-Way Experiments 210
6.6 Factorial Designs 213
6.7 Multi-Way Classification ANOVA with MINITAB 215
6.8 Design Considerations for Multi-Way Classification Designs 227
Chapter 7 Advanced ANOVA Topics 231
7.1 Incomplete Factorial Designs 231
7.2 Latin Squares and Other Squares 232
7.3 Fixed and Random Variables 235
7.4 Nested Designs 248
7.5 Power Calculations 250
Chapter 8 Linear Regression 273
8.1 Introduction 273
8.2 Linear Regression Rationale 273
8.3 Regression Coefficients 277
8.4 Linear Regression Assumptions 282
8.5 Hypothesis Tests for Regression Coefficients 285
8.6 Confidence Limits for the Regression Line 289
8.7 Prediction Limits for the Observed Values 290
8.8 Correlation 293
8.9 Linear Regression with MINITAB 299
8.10 Transformations to Linear Form 301
8.11 Polynomial Models 306
8.12 Goodness of Fit Tests 309
8.13 Errors in Variables 316
8.14 Weighted Regression 317
8.15 Coded Variables 318
8.16 Multiple Regression 320
8.17 General Linear Models 327
8.18 Sample Size Calculations for Linear Regression 337
8.19 Design Considerations for Linear Regression 345
Chapter 9 Two-Level Factorial Experiments 347
9.1 Introduction 347
9.2 The 2[superscript 1] Factorial Experiment 347
9.3 The 2[superscript 2] Factorial Experiment 351
9.4 The 2[superscript 3] Factorial Design 362
9.5 The Addition of Center Cells to 2[superscript k] Designs 367
9.6 General Procedure for Analysis of 2[superscript k] Designs 370
9.7 2[superscript k] Factorial Designs in MINITAB 372
9.8 Extra and Missing Values 389
9.9 Propagation of Error 390
9.10 Sample Size and Power 392
9.11 Design Considerations for 2[superscript k] Experiments 397
Chapter 10 Fractional Factorial Experiments 399
10.1 Introduction 399
10.2 The 2[superscript 5-1] Half-Fractional Factorial Design 400
10.3 Other Fractional Factorial Designs 406
10.4 Design Resolution 407
10.5 The Consequences of Confounding 411
10.6 Fractional Factorial Designs in MINITAB 415
10.7 Interpretation of Fractional Factorial Designs 421
10.8 Plackett-Burman Designs 432
10.9 Sample-Size Calculations 432
10.10 Design Considerations for Fractional Factorial Experiments 434
Chapter 11 Response-Surface Experiments 437
11.1 Introduction 437
11.2 Terms in Quadratic Models 438
11.3 2[superscript k] Designs with Centers 441
11.4 3[superscript k] Factorial Designs 443
11.5 Box-Behnken Designs 444
11.6 Central Composite Designs 448
11.7 Comparison of the Response-Surface Designs 453
11.8 Response Surface Designs in MINITAB 458
11.9 Sample-Size Calculations 466
11.10 Design Considerations for Response-Surface Experiments 474
Appendix A Statistical Tables 477
A.1 Greek Characters 477
A.2 Normal Distribution: Values of p = [Phi (-infinity less than sign z less than sign z subscript p]) 478
A.3 Student's t Distribution: Values of t[subscript p] where P ([t subscript p less than sign t less than sign infinity]) = p 480
A.4 X[superscript 2] Distribution: Values of X[superscript 2 subscript p] where P ([0 less than sign X superscript 2 less than sign X superscript 2 subscript p]) = p 481
A.5 F Distribution: Values of F[subscript p] where P ([F subscript p less than sign F less than sign infinity]) = p 482
A.6 Critical Values for Duncan's Multiple Range Test [characters not reproducible] 484
A.7 Critical Values of the Studentized Range Distribution (Q[subscript 0.05](k)) 485
A.8 Critical Values for the One-Way Analysis of Means [characters not reproducible] 486
A.9 Fisher's Z Transformation: Values of Z = 1/2ln(1+r / 1-r) 487
Bibliography 489
Index 491
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