Design and Analysis of Experiments 9th Edition, ISBN-13: 978-111911347

Description

Design and Analysis of Experiments 9th Edition by Douglas C. Montgomery, ISBN-13: 978-111911347

[PDF eBook eTextbook]

752 pages

Publisher: Wiley; 9 edition (March 13, 2017)

Language: English

ISBN-10: 1119113474

ISBN-13: 978-1119113478

Design and Analysis of Experiments, 9th Edition continues to help senior and graduate students in engineering, business, and statistics-as well as working practitioners-to design and analyze experiments for improving the quality, efficiency and performance of working systems. This bestselling text maintains its comprehensive coverage by including: new examples, exercises, and problems (including in the areas of biochemistry and biotechnology); new topics and problems in the area of response surface; new topics in nested and split-plot design; and the residual maximum likelihood method is now emphasized throughout the book.

Table of contents:

Preface……Page 3

Contents……Page 8

Strategy of Experimentation……Page 15

Some Typical Applications of Experimental Design……Page 21

Basic Principles……Page 25

Guidelines for Designing Experiments……Page 27

Brief History of Statistical Design……Page 33

Summary – using Statistical Techniques in Experimentation……Page 34

Problems……Page 35

Simple Comparative Experiments……Page 37

Introduction……Page 38

Basic Statistical Concepts……Page 39

Sampling & Sampling Distributions……Page 42

Inferences about the Differences in Means, Randomized Designs……Page 47

Inferences about the Differences in Means, Paired Comparison Designs……Page 64

Inferences about the Variances of Normal Distributions……Page 67

Problems……Page 69

Example……Page 79

The Analysis of Variance……Page 81

Analysis of the Fixed Effects Model……Page 83

Model Adequacy Checking……Page 92

Practical Interpretation of Results……Page 100

Sample Computer Output……Page 113

Determining Sample Size……Page 117

Other Examples of Single-Factor Experiments……Page 119

The Random Effects Model……Page 125

The Regression Approach to the Analysis of Variance……Page 133

Nonparametric Methods in the Analysis of Variance……Page 137

Problems……Page 139

The Randomized Complete Block Design……Page 149

The Latin Square Design……Page 167

The Graeco-Latin Square Design……Page 174

Balanced Incomplete Block Designs……Page 176

Problems……Page 185

Basic Definitionsand Principles……Page 193

The Advantage of Factorials……Page 196

The Two-Factor Factorial Design……Page 197

The General Factorial Design……Page 215

Fitting Response Curves and Surfaces……Page 220

Blocking in a Factorial Design……Page 229

Problems……Page 234

Introduction……Page 244

2^2 Design……Page 245

2^3 Design……Page 254

General 2^k Design……Page 266

Single Replicate of 2^k Design……Page 268

Additional Examples of Unreplicated 2^k Desidns……Page 282

Designs are Optimal Designs……Page 294

Addition of Center Points to 2^k Designs……Page 299

Why Coded Design Variables……Page 304

Problems……Page 306

Introduction……Page 322

Factorial Design……Page 323

Factorial Design in Two Blocks……Page 325

Another Illustration of Why Blocking Is Important……Page 333

Factorial Design in Four Blocks……Page 334

Blocks……Page 336

Partial Confounding……Page 337

Problems……Page 339

Two-Level Fractional Factorial Designs……Page 342

Design……Page 343

Design……Page 358

Fractional Factorial Design……Page 365

Alias Structures in Fractional Factorials and Other Designs……Page 374

Resolution III Designs……Page 376

Resolution IV and V Designs……Page 390

Supersaturated Designs……Page 398

Summary……Page 399

Problems……Page 400

3^k Factorial Design……Page 420

Factorial Design……Page 427

Factorial Design……Page 432

Factorials with Mixed Levels……Page 436

Nonregular Fractional Factorial Designs……Page 439

Constructing Factorial and Fractional Factorial Designs Using an Optimal Design Tool……Page 456

Problems……Page 468

Fitting Regression Models……Page 474

Linear Regression Models……Page 475

Estimation of the Parameters in Linear Regression Models……Page 476

Hypothesis Testing in Multiple Regression……Page 487

ConfidenceIntervals in Multiple Regression……Page 492

Prediction of New Response Observations……Page 493

Regression Model Diagnostics……Page 494

Testing for Lack of Fit……Page 497

Problems……Page 499

Response Surface Methods & Designs……Page 503

Intro to Response Surface Methodology……Page 504

The Method of Steepest Ascent……Page 506

Analysis of a Second-Order Response Surface……Page 511

Experimental Designs for Fitting Response Surfaces……Page 525

Experiments with Computer Models……Page 549

Mixture Experiments……Page 556

Evolutionary Operation……Page 567

Problems……Page 572

Introduction……Page 583

Crossed Array Designs……Page 585

Analysis of the Crossed Array Design……Page 587

Combined Array Designs and the Response Model Approach……Page 590

Choice of Designs……Page 596

Problems……Page 599

Random Effects Models……Page 603

The Two-Factor Factorial with Random Factors……Page 604

The Two-Factor Mixed Model……Page 611

Rules for Expected Mean Squares……Page 616

Approximate F-Tests……Page 619

Additional Topics on Estimation of Variance Components……Page 623

Problems……Page 629

Nested & Split-Plot Designs……Page 632

The Two-Stage Nested Design……Page 633

General m-Stage Nested Design……Page 642

Designs with Both Nested and Factorial Factors……Page 644

The Split-Plot Design……Page 648

Other Variations of the Split-Plot Design……Page 654

Problems……Page 664

Nonnormal Responses & Transformations……Page 671

Unbalanced Data in Factorial Design……Page 680

Analysis of Covariance……Page 684

Repeated Measures……Page 706

Problems……Page 708

Appendix……Page 711

Biblio……Page 738

Index……Page 745

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