design and analysis of experiments by douglas c. montgomery

• General & Introductory Industrial Engineering

Design and Analysis of Experiments, 10th Edition

ISBN: 978-1-119-49244-3

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Douglas C. Montgomery

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.

• New Enhanced E-Text with added resources to make your study time more effective, including the ability to show/hide solutions for selected practice problems, helpful videos, supplemental text material linked from the e-text, and data sets linked from the e-text
• Revised and updated student problems are now presented at the beginning of chapters
• Selected problems have been reserved for instructor use
• Embedded links provide access to supplemental material, including new video content, study guide, and lecture slides
• Revised throughout for increased accuracy and up-to-date references
• Focuses on practical applications of widely-used software tools, including examples from Design-Expert, Minitab, JMP, and SAS
• Demonstrates how models are developed from experimental data
• Emphasizes the utility of experimental design to enhance product and process design, development, and optimization
• Covers all major design techniques, using a balanced approach to both design and analysis
• Presents multiple examples of both traditional and cutting-edge methods, providing foundational knowledge that translates directly to real-world skills

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Book description

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

• About the Book
• Course Suggestions
• The Supplemental Text Material
• Acknowledgments
• 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
• 2.1 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
• 3.1 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
• 4.1 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
• 5.1 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
• 6.1 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 Why We Work with Coded Design Variables
• 6.10 Problems
• 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
• 8.1 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
• 9.1 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
• 10.1 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
• 11.1 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
• 12.1 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
• 13.1 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 Approximate F‐Tests
• 13.6 Some Additional Topics on Estimation of Variance Components
• 13.7 Problems
• 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
• 15.1 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
• Bibliography
• End User License Agreement

Product information

• Title: Design and Analysis of Experiments, 9th Edition
• Author(s): Douglas C. Montgomery
• Release date: May 2017
• Publisher(s): Wiley
• ISBN: 9781119320937

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Design and Analysis of Experiments Paperback – April 2, 2019

• Language English
• Publisher John Wiley & Sons
• Publication date April 2, 2019
• Dimensions 8.11 x 1.6 x 9.96 inches
• ISBN-10 1119589061
• ISBN-13 978-1119589068
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Product details

• Publisher ‏ : ‎ John Wiley & Sons; 9th EMEA edition (April 2, 2019)
• Language ‏ : ‎ English
• ISBN-10 ‏ : ‎ 1119589061
• ISBN-13 ‏ : ‎ 978-1119589068
• Item Weight ‏ : ‎ 3.48 pounds
• Dimensions ‏ : ‎ 8.11 x 1.6 x 9.96 inches
• #7,187 in Mechanical Engineering (Books)
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