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Synopsis
This is an introductory text for scientists working in agriculture and experimental biology. It is appropriate for use as a textbook for undergraduate or postgraduate students of these subjects and includes all the basic statistical methods which are appropriate to the work of such scientists. The book also includes material on more advanced topics not usually discussed in an introductory text, including multiple regression, incomplete block experimental design, confounded and split-plot experimental designs, non-linear and log-linear models, and repeated measurements. The authors believe that research scientists should be aware of the potential benefits of these more advanced methods in their work. The second edition includes new material on the effective use of computers for statistical analysis, and shows how information is provided for, and obtained from, statistical packages. There is increased emphasis on the role of models in analyzing data, and on the flexibility provided by general linear model procedures in computer packages. There is also a new chapter on the analysis of multiple and repeated measurements. The book lays particular emphasis on the assumptions implicit in statistical methods and includes a chapter devoted solely to this important aspect. It also emphasizes the importance of designing experiments properly, particularly in using small, natural blocks and factorial treatment structure, and of using available resources efficiently. Throughout the book, the authors concentrate on the understanding needed for using statistical methods and for using statistical computer packages. The methods and the interpretation of results are illustrated by carefully described worked examples and further data sets are provided as exercises for the reader.
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Présentation de l'éditeur
The third edition of this popular introductory text maintains the character that won worldwide respect for its predecessors but features a number of enhancements that broaden its scope, increase its utility, and bring the treatment thoroughly up to date. It provides complete coverage of the statistical ideas and methods essential to students in agriculture or experimental biology. In addition to covering fundamental methodology, this treatment also includes more advanced topics that the authors believe help develop an appreciation of the breadth of statistical methodology now available. The emphasis is not on mathematical detail, but on ensuring students understand why and when various methods should be used.
New in the Third Edition:
Présentation de l'éditeur
An introductory text for scientists working in agriculture and experimental biology, Statistical Methods in Agriculture and Experimental Biology includes all the basic statistical methods relevant to their work. Undergraduate and postgraduate majors in those subjects will find its information most essential to their studies.
Material on more advanced topics- not usually discussed in an introductory text-focuses on multiple regression, incomplete block experimental design, confounded and split-plot experimental designs, non-linear and log-linear models, and repeated measurements. The authors believe that research scientists should be aware of the potential benefits of those more advanced methods in their work.
Particular emphasis is placed upon the assumptions implicit in statistical methods: a full chapter is devoted to that important aspect. It also stresses the importance of designing experiments properly, particularly in using small, natural blocks and factorial treatment structure, and of using available resources efficiently, and extracting all information from the data.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.