Design and Analysis of Experiments, 10ed, An Indian Adaptation
Description
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.
Table of Contents
1 Introduction
1.1 Strategy of Experimentation
1.2 A Brief History of Statistical Design
1.3 Some Applications of Experimental Design
1.4 Basic Principles of Experimentation
1.5 Guidelines for Designing Experiments
1.6 Summary: Using Statistical Techniques in Experimentation
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
Problems
3 Single-Factor Analysis of Variance: ANOVA
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 ANOVA
3.11 Nonparametric Methods in the Analysis of Variance
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
Problems
5 Introduction to Factorial Designs
5.1 Basic Definitions and Principles of Factorial Designs
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
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 Designs
6.7 2k Designs Are Optimal Designs
6.8 The Addition of Center Points to the 2k Design
6.9 Benefits of Working with Coded Design Variables
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 Illustration on Importance of Blocking
7.6 Confounding the 2k Factorial Design in Four Blocks
7.7 Confounding the 2k Factorial Design in 2p Blocks
7.8 Partial Confounding
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
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
Problems
10 Regression Models
10.1 Introduction
10.2 Linear Regression Models
10.3 Estimation of the Parameters in Linear Regression Models
10.4 Polynomial Regression Models
10.5 Hypothesis Testing in Multiple Regression
10.6 Confidence Intervals in Multiple Regression
10.7 Prediction of New Response Observations
10.8 Regression Model Diagnostics
10.9 Testing for Lack of Fit
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
Problems
12 Robust Parameter Design and Process Robustness Studies
12.1 Introduction
12.2 Source of Noise in Functional Variation
12.3 Crossed Array Designs
12.4 Analysis of the Crossed Array Design
12.5 Combined Array Designs and the Response Model Approach
12.6 Choice of Designs
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 Rules for Expected Mean Squares
13.5 Block Designs and Random Block Effects
13.6 Approximate F-Tests
13.7 Some Additional Topics on Estimation of Variance Components
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 Nested Fixed Effects and Random Effects
14.5 The Split-Plot Design
14.6 Other Variations of the Split-Plot Design
Problems
15 Other Design and Analysis Topics (available online)
Multiple-Choice Questions
Answer to Multiple-Choice
Questions ANS
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 Percentage Points of the Studentized Range Statistic
Table VI Critical Values for Dunnett’s Test for Comparing Treatments with a Control
Table VII Coefficients of Orthogonal Polynomials
Table VIII Alias Relationships for 2k−p Fractional Factorial Designs with k ≤ 15 and n ≤ 64
Bibliography (available online)
Index