# Design and analysis of experiments / Douglas C. Montgomery, Arizona State University.

##### By: Montgomery, Douglas C

Material type: TextLanguage: English Publisher: Hoboken, NJ : John Wiley & Sons, Inc., [2013]; New Delhi: Wiley India Pvt. Ltd.; 2013Edition: Eighth editionDescription: xvii, 730 pages : illustrations ; 26 cmISBN: 9788126540501; 9781118146927 (hbk. : acidfree paper)Subject(s): Experimental design | TECHNOLOGY & ENGINEERING / Industrial EngineeringDDC classification: 519.57 LOC classification: QA279 | .M66 2013Other classification: TEC009060 Online resources: Table of contents only | Publisher description | WorldCat Details | E-book FulltextItem type | Current location | Collection | Call number | Copy number | Status | Date due | Barcode | Item holds |
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Includes bibliographical references (pages 719-724) and index.

Table of contents Preface --

1 Introduction --

1.1 Strategy of Experimentation --

1.2 Some Typical Applications of Experimental Design --

1.3 Basic Principles --

1.4 Guidelines for Designing Experiments --

1.5 A Brief History of Statistical Design --

1.6 Summary: Using Statistical Techniques in Experimentation --

1.7 Problems --

2 Simple Comparative Experiments --

2.1 Introduction --

2.2 Basic Statistical Concepts --

2.3 Sampling and Sampling Distributions --

2.4 Inferences About the Differences in Means, Randomized Designs --

2.5 Inferences About the Differences in Means, Paired Comparison Designs --

2.6 Inferences About the Variances of Normal Distributions --

2.7 Problems --

3 Experiments with a Single Factor: The Analysis of Variance --

3.1 An Example --

3.2 The Analysis of Variance --

3.3 Analysis of the Fixed Effects Model --

3.4 Model Adequacy Checking --

3.5 Practical Interpretation of Results --

3.6 Sample Computer Output --

3.7 Determining Sample Size --

3.8 Other Examples of Single-Factor Experiments --

3.9 The Random Effects Model --

3.10 The Regression Approach to the Analysis of Variance --

3.11 Nonparametric Methods in the Analysis of Variance --

3.12 Problems --

4 Randomized Blocks, Latin Squares, and Related Designs --

4.1 The Randomized Complete Block Design --

4.2 The Latin Square Design --

4.3 The Graeco-Latin Square Design --

4.4 Balanced Incomplete Block Designs --

4.5 Problems --

5 Introduction to Factorial Designs. 5.1 Basic Definitions and Principles --

5.2 The Advantage of Factorials --

5.3 The Two-Factor Factorial Design --

5.4 The General Factorial Design --

5.5 Fitting Response Curves and Surfaces --

5.6 Blocking in a Factorial Design --

5.7 Problems --

6 The 2k Factorial Design --

6.1 Introduction --

6.2 The 22 Design --

6.3 The 23 Design --

6.4 The General 2k Design --

6.5 A Single Replicate of the 2k Design --

6.6 Additional Examples of Unreplicated 2k Design --

6.7 2k Designs are Optimal Designs --

6.8 The Addition of Center Points to the 2k Design --

6.9 Why We Work with Coded Design Variables --

6.10 Problems --

7 Blocking and Confounding in the 2k Factorial Design --

7.1 Introduction --

7.2 Blocking a Replicated 2k Factorial Design --

7.3 Confounding in the 2k Factorial Design --

7.4 Confounding the 2k Factorial Design in Two Blocks --

7.5 Another Illustration of Why Blocking Is Important --

7.6 Confounding the 2k Factorial Design in Four Blocks --

7.7 Confounding the 2k Factorial Design in 2p Blocks --

7.8 Partial Confounding --

7.9 Problems --

8 Two-Level Fractional Factorial Designs --

8.1 Introduction --

8.2 The One-Half Fraction of the 2k Design --

8.3 The One-Quarter Fraction of the 2k Design --

8.4 The General 2k_p Fractional Factorial Design --

8.5 Alias Structures in Fractional Factorials and other Designs --

8.6 Resolution III Designs --

8.7 Resolution IV and V Designs --

8.8 Supersaturated Designs --

8.9 Summary --

8.10 Problems. 9 Additional Design and Analysis Topics for Factorial and Fractional Factorial Designs --

9.1 The 3k Factorial Design --

9.2 Confounding in the 3k Factorial Design --

9.3 Fractional Replication of the 3k Factorial Design --

9.4 Factorials with Mixed Levels --

9.5 Nonregular Fractional Factorial Designs --

9.6 Constructing Factorial and Fractional Factorial Designs Using an Optimal Design Tool --

9.7 Problems --

10 Fitting Regression Models --

10.1 Introduction --

10.2 Linear Regression Models --

10.3 Estimation of the Parameters in Linear Regression Models --

10.4 Hypothesis Testing in Multiple Regression --

10.5 Confidence Intervals in Multiple Regression --

10.6 Prediction of New Response Observations --

10.7 Regression Model Diagnostics --

10.8 Testing for Lack of Fit --

10.9 Problems --

11 Response Surface Methods and Designs --

11.1 Introduction to Response Surface Methodology --

11.2 The Method of Steepest Ascent --

11.3 Analysis of a Second-Order Response Surface --

11.4 Experimental Designs for Fitting Response Surfaces --

11.5 Experiments with Computer Models --

11.6 Mixture Experiments --

11.7 Evolutionary Operation --

11.8 Problems --

12 Robust Parameter Design and Process Robustness Studies --

12.1 Introduction --

12.2 Crossed Array Designs --

12.3 Analysis of the Crossed Array Design --

12.4 Combined Array Designs and the Response Model Approach --

12.5 Choice of Designs --

12.6 Problems --

13 Experiments with Random Factors. 13.1 Random Effects Models --

13.2 The Two-Factor Factorial with Random Factors --

13.3 The Two-Factor Mixed Model --

13.4 Sample Size Determination with Random Effects --

13.5 Rules for Expected Mean Squares --

13.6 Approximate F Tests --

13.7 Some Additional Topics on Estimation of Variance Components --

13.8 Problems --

14 Nested and Split-Plot Designs --

14.1 The Two-Stage Nested Design --

14.2 The General m-Stage Nested Design --

14.3 Designs with Both Nested and Factorial Factors --

14.4 The Split-Plot Design --

14.5 Other Variations of the Split-Plot Design --

14.6 Problems --

15 Other Design and Analysis Topics. 15.1 Nonnormal Responses and Transformations --

15.2 Unbalanced Data in a Factorial Design --

15.3 The Analysis of Covariance --

15.4 Repeated Measures --

15.5 Problems --

Appendix --

Table I. Cumulative Standard Normal Distribution --

Table II. Percentage Points of the t Distribution --

Table III. Percentage Points of the _2 Distribution --

Table IV. Percentage Points of the F Distribution --

Table V. Operating Characteristic Curves for the Fixed Effects Model Analysis of Variance --

Table VI. Operating Characteristic Curves for the Random Effects Model Analysis of Variance --

Table VII. Percentage Points of the Studentized Range Statistic --

Table VIII. Critical Values for Dunnett's Test for Comparing Treatments with a Control --

Table IX. Coefficients of Orthogonal Polynomials --

Table X. Alias Relationships for 2k_p Fractional Factorial Designs with k 15 and n 64 --

Bibliography --

Index.

"The eighth edition of Design and Analysis of Experiments continues to provide extensive and in-depth information on engineering, business, and statistics-as well as informative ways to help readers design and analyze experiments for improving the quality, efficiency and performance of working systems. Furthermore, the 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"--

Applied Statistics

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