Design and Analysis of Experiments, EMEA Edition

Name: Design and Analysis of Experiments, EMEA Edition
SKU: 9781119816959
Price: 749 SEK
Availability: InStock
Author: Douglas C. Montgomery
ISBN: 9781119816959

Häftad, Engelska, 2021

AvDouglas C. Montgomery

749 kr

Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.

Design and Analysis of Experiments provides a rigorous introduction to product and process design improvement through quality and performance optimization. Clear demonstration of widely practiced techniques and procedures allows readers to master fundamental concepts, develop design and analysis skills, and use experimental models and results in real-world applications. Detailed coverage of factorial and fractional factorial design, response surface techniques, regression analysis, biochemistry and biotechnology, single factor experiments, and other critical topics offer highly-relevant guidance through the complexities of the field. Stressing the importance of both conceptual knowledge and practical skills, this text adopts a balanced approach to theory and application. Extensive discussion of modern software tools integrate data from real-world studies, while examples illustrate the efficacy of designed experiments across industry lines, from service and transactional organizations to heavy industry and biotechnology. Broad in scope yet deep in detail, this text is both an essential student resource and an invaluable reference for professionals in engineering, science, manufacturing, statistics, and business management.

Produktinformation

Utgivningsdatum2021-07-08
Mått10 x 10 x 10 mm
Vikt454 g
FormatHäftad
SpråkEngelska
Antal sidor688
Upplaga10
FörlagJohn Wiley & Sons Inc
ISBN9781119816959

Tillhör följande kategorier

Tillverkningsteknik inom Naturvetenskap och teknik

Preface iii1 Introduction 11.1 Strategy of Experimentation 11.2 Some Typical Applications of Experimental Design 71.3 Basic Principles 111.4 Guidelines for Designing Experiments 131.5 A Brief History of Statistical Design 191.6 Summary: Using Statistical Techniques in Experimentation 202 Simple Comparative Experiments 222.1 Introduction 222.2 Basic Statistical Concepts 232.3 Sampling and Sampling Distributions 272.4 Inferences About the Differences in Means, Randomized Designs 322.5 Inferences About the Differences in Means, Paired Comparison Designs 472.6 Inferences About the Variances of Normal Distributions 523 Experiments with a Single Factor: The Analysis of Variance 553.1 An Example 553.2 The Analysis of Variance 583.3 Analysis of the Fixed Effects Model 593.4 Model Adequacy Checking 683.5 Practical Interpretation of Results 763.6 Sample Computer Output 893.7 Determining Sample Size 933.8 Other Examples of Single-Factor Experiments 953.9 The Random Effects Model 1013.10 The Regression Approach to the Analysis of Variance 1093.11 Nonparametric Methods in the Analysis of Variance 1134 Randomized Blocks, Latin Squares, and Related Designs 1154.1 The Randomized Complete Block Design 1154.2 The Latin Square Design 1334.3 The Graeco-Latin Square Design 1404.4 Balanced Incomplete Block Designs 1425 Introduction to Factorial Designs 1525.1 Basic Definitions and Principles 1525.2 The Advantage of Factorials 1555.3 The Two-Factor Factorial Design 1565.4 The General Factorial Design 1745.5 Fitting Response Curves and Surfaces 1795.6 Blocking in a Factorial Design 1886 The 2k Factorial Design 1946.1 Introduction 1946.2 The 22 Design 1956.3 The 23 Design 2036.4 The General 2k Design 2156.5 A Single Replicate of the 2k Design 2186.6 Additional Examples of Unreplicated 2k Designs 2316.7 2k Designs are Optimal Designs 2436.8 The Addition of Center Points to the 2k Design 2486.9 Why We Work with Coded Design Variables 2537 Blocking and Confounding in the 2k Factorial Design 2567.1 Introduction 2567.2 Blocking a Replicated 2k Factorial Design 2567.3 Confounding in the 2k Factorial Design 2597.4 Confounding the 2k Factorial Design in Two Blocks 2597.5 Another Illustration of Why Blocking is Important 2677.6 Confounding the 2k Factorial Design in Four Blocks 2687.7 Confounding the 2k Factorial Design in 2p Blocks 2707.8 Partial Confounding 2718 Two-Level Fractional Factorial Designs 2748.1 Introduction 2748.2 The One-Half Fraction of the 2k Design 2758.3 The One-Quarter Fraction of the 2k Design 2908.4 The General 2k--pFractional Factorial Design 2978.5 Alias Structures in Fractional Factorials and Other Designs 3068.6 Resolution III Designs 3088.7 Resolution IV and V Designs 3228.8 Supersaturated Designs 3298.9 Summary 3319 Additional Design and Analysis Topics for Factorial and Fractional Factorial Designs 3329.1 The 3k Factorial Design 3339.2 Confounding in the 3k Factorial Design 3409.3 Fractional Replication of the 3k Factorial Design 3459.4 Factorials with Mixed Levels 3499.5 Nonregular Fractional Factorial Designs 3529.6 Constructing Factorial and Fractional Factorial Designs Using an Optimal Design Tool 36910 Fitting Regression Models 38210.1 Introduction 38210.2 Linear Regression Models 38310.3 Estimation of the Parameters in Linear Regression Models 38410.4 Hypothesis Testing in Multiple Regression 39510.5 Confidence Intervals in Multiple Regression 39910.6 Prediction of New Response Observations 40110.7 Regression Model Diagnostics 40210.8 Testing for Lack of Fit 40511 Response Surface Methods and Designs 40811.1 Introduction to Response Surface Methodology 40811.2 The Method of Steepest Ascent 41111.3 Analysis of a Second-Order Response Surface 41611.4 Experimental Designs for Fitting Response Surfaces 43011.5 Experiments with Computer Models 45411.6 Mixture Experiments 46111.7 Evolutionary Operation 47212 Robust Parameter Design and Process Robustness Studies 47712.1 Introduction 47712.2 Crossed Array Designs 47912.3 Analysis of the Crossed Array Design 48112.4 Combined Array Designs and the Response Model Approach 48412.5 Choice of Designs 49013 Experiments with Random Factors 49313.1 Random Effects Models 49313.2 The Two-Factor Factorial with Random Factors 49413.3 The Two-Factor Mixed Model 50013.4 Rules for Expected Mean Squares 50513.5 Approximate F-Tests 50813.6 Some Additional Topics on Estimation of Variance Components 51214 Nested and Split-Plot Designs 51814.1 The Two-Stage Nested Design 51814.2 The General m-Stage Nested Design 52814.3 Designs with Both Nested and Factorial Factors 53014.4 The Split-Plot Design 53414.5 Other Variations of the Split-Plot Design 54015 Other Design and Analysis Topics (Available in e-text for students) W-1Problems P-1Appendix A-1Table I. Cumulative Standard Normal Distribution A-2Table II. Percentage Points of the t Distribution A-4Table III. Percentage Points of the Χ 2 Distribution A-5Table IV. Percentage Points of the F Distribution A-6Table V. Percentage Points of the Studentized Range Statistic A-11Table VI. Critical Values for Dunnett's Test for Comparing Treatments with a Control A-13Table VII. Coefficients of Orthogonal Polynomials A-15Table VIII. Alias Relationships for 2k--pFractional Factorial Designs with k ≤ 15 and n ≤ 64 A-16OC Bibliography (Available in e-text for students) B-1Index I-1

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Design and Analysis of Experiments, EMEA Edition

Häftad, Engelska, 2021

AvDouglas C. Montgomery

749 kr

Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.

Produktinformation

Utgivningsdatum2021-07-08
Mått10 x 10 x 10 mm
Vikt454 g
FormatHäftad
SpråkEngelska
Antal sidor688
Upplaga10
FörlagJohn Wiley & Sons Inc
ISBN9781119816959

Tillhör följande kategorier

Tillverkningsteknik inom Naturvetenskap och teknik

Preface iii1 Introduction 11.1 Strategy of Experimentation 11.2 Some Typical Applications of Experimental Design 71.3 Basic Principles 111.4 Guidelines for Designing Experiments 131.5 A Brief History of Statistical Design 191.6 Summary: Using Statistical Techniques in Experimentation 202 Simple Comparative Experiments 222.1 Introduction 222.2 Basic Statistical Concepts 232.3 Sampling and Sampling Distributions 272.4 Inferences About the Differences in Means, Randomized Designs 322.5 Inferences About the Differences in Means, Paired Comparison Designs 472.6 Inferences About the Variances of Normal Distributions 523 Experiments with a Single Factor: The Analysis of Variance 553.1 An Example 553.2 The Analysis of Variance 583.3 Analysis of the Fixed Effects Model 593.4 Model Adequacy Checking 683.5 Practical Interpretation of Results 763.6 Sample Computer Output 893.7 Determining Sample Size 933.8 Other Examples of Single-Factor Experiments 953.9 The Random Effects Model 1013.10 The Regression Approach to the Analysis of Variance 1093.11 Nonparametric Methods in the Analysis of Variance 1134 Randomized Blocks, Latin Squares, and Related Designs 1154.1 The Randomized Complete Block Design 1154.2 The Latin Square Design 1334.3 The Graeco-Latin Square Design 1404.4 Balanced Incomplete Block Designs 1425 Introduction to Factorial Designs 1525.1 Basic Definitions and Principles 1525.2 The Advantage of Factorials 1555.3 The Two-Factor Factorial Design 1565.4 The General Factorial Design 1745.5 Fitting Response Curves and Surfaces 1795.6 Blocking in a Factorial Design 1886 The 2k Factorial Design 1946.1 Introduction 1946.2 The 22 Design 1956.3 The 23 Design 2036.4 The General 2k Design 2156.5 A Single Replicate of the 2k Design 2186.6 Additional Examples of Unreplicated 2k Designs 2316.7 2k Designs are Optimal Designs 2436.8 The Addition of Center Points to the 2k Design 2486.9 Why We Work with Coded Design Variables 2537 Blocking and Confounding in the 2k Factorial Design 2567.1 Introduction 2567.2 Blocking a Replicated 2k Factorial Design 2567.3 Confounding in the 2k Factorial Design 2597.4 Confounding the 2k Factorial Design in Two Blocks 2597.5 Another Illustration of Why Blocking is Important 2677.6 Confounding the 2k Factorial Design in Four Blocks 2687.7 Confounding the 2k Factorial Design in 2p Blocks 2707.8 Partial Confounding 2718 Two-Level Fractional Factorial Designs 2748.1 Introduction 2748.2 The One-Half Fraction of the 2k Design 2758.3 The One-Quarter Fraction of the 2k Design 2908.4 The General 2k--pFractional Factorial Design 2978.5 Alias Structures in Fractional Factorials and Other Designs 3068.6 Resolution III Designs 3088.7 Resolution IV and V Designs 3228.8 Supersaturated Designs 3298.9 Summary 3319 Additional Design and Analysis Topics for Factorial and Fractional Factorial Designs 3329.1 The 3k Factorial Design 3339.2 Confounding in the 3k Factorial Design 3409.3 Fractional Replication of the 3k Factorial Design 3459.4 Factorials with Mixed Levels 3499.5 Nonregular Fractional Factorial Designs 3529.6 Constructing Factorial and Fractional Factorial Designs Using an Optimal Design Tool 36910 Fitting Regression Models 38210.1 Introduction 38210.2 Linear Regression Models 38310.3 Estimation of the Parameters in Linear Regression Models 38410.4 Hypothesis Testing in Multiple Regression 39510.5 Confidence Intervals in Multiple Regression 39910.6 Prediction of New Response Observations 40110.7 Regression Model Diagnostics 40210.8 Testing for Lack of Fit 40511 Response Surface Methods and Designs 40811.1 Introduction to Response Surface Methodology 40811.2 The Method of Steepest Ascent 41111.3 Analysis of a Second-Order Response Surface 41611.4 Experimental Designs for Fitting Response Surfaces 43011.5 Experiments with Computer Models 45411.6 Mixture Experiments 46111.7 Evolutionary Operation 47212 Robust Parameter Design and Process Robustness Studies 47712.1 Introduction 47712.2 Crossed Array Designs 47912.3 Analysis of the Crossed Array Design 48112.4 Combined Array Designs and the Response Model Approach 48412.5 Choice of Designs 49013 Experiments with Random Factors 49313.1 Random Effects Models 49313.2 The Two-Factor Factorial with Random Factors 49413.3 The Two-Factor Mixed Model 50013.4 Rules for Expected Mean Squares 50513.5 Approximate F-Tests 50813.6 Some Additional Topics on Estimation of Variance Components 51214 Nested and Split-Plot Designs 51814.1 The Two-Stage Nested Design 51814.2 The General m-Stage Nested Design 52814.3 Designs with Both Nested and Factorial Factors 53014.4 The Split-Plot Design 53414.5 Other Variations of the Split-Plot Design 54015 Other Design and Analysis Topics (Available in e-text for students) W-1Problems P-1Appendix A-1Table I. Cumulative Standard Normal Distribution A-2Table II. Percentage Points of the t Distribution A-4Table III. Percentage Points of the Χ 2 Distribution A-5Table IV. Percentage Points of the F Distribution A-6Table V. Percentage Points of the Studentized Range Statistic A-11Table VI. Critical Values for Dunnett's Test for Comparing Treatments with a Control A-13Table VII. Coefficients of Orthogonal Polynomials A-15Table VIII. Alias Relationships for 2k--pFractional Factorial Designs with k ≤ 15 and n ≤ 64 A-16OC Bibliography (Available in e-text for students) B-1Index I-1