Design and Analysis of Experiments, 8/e (IE-Paperback)
Douglas C. Montgomery
- 出版商: Wiley
- 出版日期: 2012-05-01
- 定價: $1,620
- 售價: 9.8 折 $1,588
- 語言: 英文
- 頁數: 752
- ISBN: 1118097939
- ISBN-13: 9781118097939
-
相關分類:
Data Science、機率統計學 Probability-and-statistics
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相關主題
商品描述
本書序言
●The residual maximum likelihood (REML) method is now emphasized throughout the book.
●83 new homework problems (including in the areas of biochemistry and biotechnology).
●Additional examples of single-factor experiments, such as a study involving chocolate consumption and cardiovascular health (Chapter 3)
●New section on the random effects model (Chapter 3)
●New material on nonregular fractions as alternatives to traditional minimum aberration fractions in 16 runs and analysis methods for those designs discussed and illustrated (Chapter 9).
●New material on constructing factorial and fractional factorial designs using an optimal design tool (Chapter 9).
●New topics and problems in the area of response surface, including designs that combine screening and optimization and use of optimal designs (Chapter 11).
●New topics in nested and split-plot design, including the use of REML in the analysis (Chapter 14).
本書特色
●Includes software examples taken from the four most dominant programs in the field: Design-Expert, Minitab, JMP, and SAS.
●Focuses on the connection between the experiment and the model that the experimenter can develop from the results of the experiement.
●Stresses the importance of experimental design as a tool for engineers and scientists to use for product design and development as well as process development and improvement. The use of experiemental design in developing products that are robust to environmental factors and other sources of variability is illustrated. The use of experimental design early in the product cycle can subsatantially reduce development lead time and cost, leading to processes and products that perform better in the field and have higher reliability than those developed using other approaches.
商品描述(中文翻譯)
本書序言
- 本書強調了剩餘最大概似法(REML)方法。
- 新增了83個新的作業問題(包括生物化學和生物技術領域)。
- 增加了單因素實驗的其他示例,例如涉及巧克力消費和心血管健康的研究(第3章)。
- 新增了關於隨機效應模型的部分(第3章)。
- 新增了關於非常規分數的材料,作為傳統最小畸變分數在16次運行和相應設計的替代方法,並討論和示範了分析方法(第9章)。
- 新增了使用最佳設計工具構建因子和分數因子設計的材料(第9章)。
- 新增了響應曲面領域的新主題和問題,包括結合篩選和優化以及使用最佳設計的設計(第11章)。
- 新增了嵌套和分割區設計的新主題,包括在分析中使用REML(第14章)。
本書特色
- 包含了從領域內四個最主要的軟體程式(Design-Expert、Minitab、JMP和SAS)中提取的軟體示例。
- 關注實驗和實驗者可以從實驗結果中開發的模型之間的聯繫。
- 強調實驗設計作為工程師和科學家在產品設計和開發以及流程開發和改進中使用的工具的重要性。示範了在開發對環境因素和其他變異源具有韌性的產品時使用實驗設計的方法。在產品週期的早期使用實驗設計可以大幅減少開發時間和成本,從而使得在現場表現更好且可靠性更高的流程和產品相比使用其他方法開發的流程和產品。
目錄大綱
1 Introduction to Designed Experiments
2 Basic Statistical Methods
3 Analysis of Variance
4 Experiments with Blocking Factors
5 Factorial Experiments
6 Two-Level Factorial Designs
7 Blocking and Confounding System for Two-Level Factorials
8 Two-Level Fractional Factorial Designs
9 Other Topics on Factorial and Fractional Factorial Designs
10 Regression Modeling
11 Response Surface Methodology
12 Robust Design
13 Random Effects Models
14 Experiments with Nested Factors and Hard-to-Change Factors
15 Other Topics
Appendix
目錄大綱(中文翻譯)
1 設計實驗介紹
2 基本統計方法
3 變異數分析
4 具有阻礙因素的實驗
5 因子實驗
6 兩層次因子設計
7 具有阻礙和混淆系統的兩層次因子設計
8 兩層次分數因子設計
9 因子和分數因子設計的其他主題
10 迴歸建模
11 響應曲面方法
12 強健設計
13 隨機效應模型
14 具有巢狀因素和難以改變因素的實驗
15 其他主題
附錄