Design and analysis of Experiments
Material type:
TextPublisher number: 2016 | Allied Informatics, JaipurPublication details: Wiley India Pvt. Ltd. India New Delhi 2015,c2013Edition: 8thDescription: 726ISBN: - 9788126540501
- 519.47 Mon
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BSDU Knowledge Resource Center, Jaipur | Not for Loan | 519.47 Mon (Browse shelf(Opens below)) | Not For Loan | 000768 | |
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BSDU Knowledge Resource Center, Jaipur | 519.47 Mon (Browse shelf(Opens below)) | Available | 000432 | ||
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BSDU Knowledge Resource Center, Jaipur | 519.47 Mon (Browse shelf(Opens below)) | Available | 000433 |
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| 518.028 553 SIV MATLAB : with Control System, Signal Processing & Image Processing Toolboxes | 519.1 MEY Introductory Probability and Statistical Applications | 519.2 LIP Schaum's Outline of Theory and Problems of Introduction to Probability and Statistics | 519.47 Mon Design and analysis of Experiments | 519.5 SPI Statistics : Schaum's Outlines | 526.3 SUB Surveying and Levelling | 526.9 DE Plane Surveying |
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, 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
• Introduction to Designed Experiments
• Basic Statistical Methods
• Analysis of Variance
• Experiments with Blocking Factors
• Factorial Experiments
• Two-Level Factorial Designs
• Blocking and Confounding Systems for Two-Level Factorials
• Two-Level Fractional Factorial Designs
• Other Topics on Factorial and Fractional Factorial Designs
• Regression Modeling
• Response Surface Methodology
• Robust Design
• Random Effects Models
• Experiments with Nested Factors and Hard-to-Change Factors
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