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## Details

Genre/Form: | Electronic books |
---|---|

Additional Physical Format: | Print version: Toutenburg, Helge. Statistical analysis of designed experiments. New York : Springer, ©2002 (DLC) 2001058976 (OCoLC)48536706 |

Material Type: | Document, Internet resource |

Document Type: | Internet Resource, Computer File |

All Authors / Contributors: |
Helge Toutenburg |

ISBN: | 0387227725 9780387227726 058547348X 9780585473482 |

OCLC Number: | 53227063 |

Description: | 1 online resource (xv, 500 pages) : illustrations. |

Contents: | Cover -- Preface -- Table of Contents -- 1. Introduction -- 2. Comparison of Two Samples -- 3. The Linear Regression Model -- 4. Single-Factor Experiments with Fixed and Random Effects -- 5. More Restrictive Designs -- 6. Multifactor Experiments -- 7. Models for Categorical Response Variables -- 8. Repeated Measures Model -- 9. Cross-Over Design -- 10. Statistical Analysis of Incomplete Data -- Appendix A -- Matrix Algebra -- Appendix B -- Theoretical Proofs -- Appendix C -- Distributions and Tables -- References. |

Series Title: | Springer texts in statistics. |

Responsibility: | Helge Toutenburg. |

More information: |

### Abstract:

## Reviews

*Editorial reviews*

Publisher Synopsis

"ï¿½This bookï¿½ is a useful reference or graduate text to complement more common choices for introductory design of experiment books the methods are logically and thoroughly developed in a rigorous, yet understandable manner. The emphasis on pharmaceutical applications throughout the book is helpful, because this continues to emerge as an important area of applications. The book would be helpful for statisticians and researchers in pharmaceutical areas once they had gained a solid understanding of the fundamentals of design of experiments." Journal of the American Statistical Association From the reviews of the second edition: "[This book] is a useful reference or graduate text to complement more common choices for introductory design of experiment books a ] the methods are logically and thoroughly developed in a rigorous, yet understandable manner. The emphasis on pharmaceutical applications throughout the book is helpful, because this continues to emerge as an important area of applications. The book would be helpful for statisticians and researchers in pharmaceutical areas once they had gained a solid understanding of the fundamentals of design of experiments." a "Journal of the American Statistical Association "The second edition of this book a ] has been reorganized with a list of topics similar to that of the first edition, but with a revised presentation and order. a ] much greater emphasis now placed on the analysis aspect of design of experiments. a ] a useful reference book or graduate text a ] . The methods are logically and thoroughly developed in a rigorous, yet understandable manner. a ] The book would be helpful for statisticians and researchers in pharmaceutical areas a ] ." (Christine M. Anderson Cook, Journal of the American Statistical Association, Vol. 98 (463), 2003) "This book is mostly concerned with the mathematical detail of the topics in the contents. There are a few sets of data, to illustrate the material; on these, SAS, S-PLUS or SPSS is used for analysis. a ] This would be an excellent book for mathematics students who take a course in statistics, or graduate statistic students a ] ." (N. R. Draper, Short Book Reviews, Vol. 23 (1), 2003) "Helge Toutenburg describes this text as a a ~resource/reference book which containsstatistical methods used by researchers in applied areas.a (TM) a ] the theory is described in a shorthand style that gets to the point without overburdening the reader with mathematical detail a ] . the author includes thorough discussions of generalized linear models (categorical data analysis) and repeated-measures designs. a ] a useful, self-contained reference for those who want a quick description of the underlying theory and practice for a large assortment of standard DOE problems." (Peter Wludyka, Technometrics, Vol. 45 (2), May, 2003) From the reviews of the second edition: "ï¿½This bookï¿½ is a useful reference or graduate text to complement more common choices for introductory design of experiment books the methods are logically and thoroughly developed in a rigorous, yet understandable manner. The emphasis on pharmaceutical applications throughout the book is helpful, because this continues to emerge as an important area of applications. The book would be helpful for statisticians and researchers in pharmaceutical areas once they had gained a solid understanding of the fundamentals of design of experiments." Journal of the American Statistical Association"The second edition of this book has been reorganized with a list of topics similar to that of the first edition, but with a revised presentation and order. much greater emphasis now placed on the analysis aspect of design of experiments. a useful reference book or graduate text . The methods are logically and thoroughly developed in a rigorous, yet understandable manner. The book would be helpful for statisticians and researchers in pharmaceutical areas ." (Christine M. Anderson Cook, Journal of the American Statistical Association, Vol. 98 (463), 2003)"This book is mostly concerned with the mathematical detail of the topics in the contents. There are a few sets of data, to illustrate the material; on these, SAS, S-PLUS or SPSS is used for analysis. This would be an excellent book for mathematics students who take a course in statistics, or graduate statistic students ." (N. R. Draper, Short Book Reviews, Vol. 23 (1), 2003)"Helge Toutenburg describes this text as a resource/reference book which contains statistical methods used by researchers inapplied areas. the theory is described in a shorthand style that gets to the point without overburdening the reader with mathematical detail . the author includes thorough discussions of generalized linear models (categorical data analysis) and repeated-measures designs. a useful, self-contained reference for those who want a quick description of the underlying theory and practice for a large assortment of standard DOE problems." (Peter Wludyka, Technometrics, Vol. 45 (2), May, 2003) Read more...

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