Experimental Design and Data Analysis for Biologists

Experimental Design and Data Analysis for Biologists
By Gerry P. Quinn,&nbspMichael J. Keough,

* Publisher: Cambridge University Press
* Number Of Pages: 520
* Publication Date: 2002-04-08
* Sales Rank: 1959265
* ISBN / ASIN: 0521811287
* EAN: 9780521811286
* Binding: Hardcover
* Manufacturer: Cambridge University Press
* Studio: Cambridge University Press

Book Description:

This essential textbook is designed for students or researchers in biology who need to design experiments, sampling programs, or analyze resulting data. The text begins with a revision of estimation and hypothesis testing methods, before advancing to the analysis of linear and generalized linear models. The chapters include such topics as linear and logistic regression, simple and complex ANOVA models, log-linear models, and multivariate techniques. The main analyses are illustrated with many examples from published papers and an extensive reference list to both the statistical and biological literature is also included. The book is supported by a web-site that provides all data sets, questions for each chapter and links to software.

Download Description:

An essential textbook for any student or researcher in biology needing to design experiments, sampling programs or analyse the resulting data. The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models. Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models. Multivariate techniques, including classification and ordination, are then introduced. Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results. The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature. The book is supported by a web-site that provides all data sets, questions for each chapter and links to software.

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