Design of experiments : a realistic approach
著者
書誌事項
Design of experiments : a realistic approach
(Statistics : textbooks and monographs, v. 5)
M. Dekker, c1974
大学図書館所蔵 全42件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographies and indexes
内容説明・目次
内容説明
The book is written for anyone who wants to design experiments, carry them out, and analyze the results. The authors provide a clear-cut, practical approach to designing experiments in any discipline and explain the general principles upon which such design is based. The reader then can apply these theories to any specific problem in his own work.
No advanced mathematics is needed to utilize Design of Experiments - the necessary statistical concepts and briefly reviewed in the first two chapters. Subsequent chapters explain why and how the design of experiments in an intrinsic part of the scientific method, what problems will be encountered by the researcher in setting up his experiment and how to deal with them, and how to accurately analyze the result in terms of the sample taken and the method used. Each chapter includes problems encountered in specific fields so that the reader can test himself on his comprehension of the material. The diversity of the applications that these problems encompass also allows the reader to grasp the basic principles that unite the statistical approach to experiment design.
Researchers and students in engineering, agriculture, pharmacy, veterinary science, chemistry, biology, the social; sciences, statistics, mathematics, or any other field that requires the design, solution, and analysis of problems will find this book absolutely indispensable.
目次
Review of Some Basic Statistical Concepts Some Intermediate Data Analysis Concepts A Scientific Approach to Experimentation Completely Randomized Design (CRD) Randomized Complete Block Design (RCBD) Nested (Hierarchical) and Nested Factorial Designs Split Plot Type Design Latin Square Type Designs 2n Factorial Experiments (Complete and Incomplete Blocks) Fractional Factorial Experiments for Two-Leveled Factors Three-Level Factorial Experiments Mixed Factorial Experiments and Other Incomplete Block Designs Response Surface Exploration Appendices
「Nielsen BookData」 より