Experimental Design and Data Analysis for Biologists [NOOK Book]

Overview

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 ...

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Experimental Design and Data Analysis for Biologists

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Overview

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.

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Editorial Reviews

From the Publisher
"This massive books fills an important niche: a reference book on advanced statistical methods for research biologists...It's impressive because it is totally new...Even more interesting is the fact that the data are actually available free for downloading from a website...there is so much packed into this book that I view it more as a reference than a textbook...it is wonderful and loaded with all the newest methods. I recommend it to readers who venture into more advanced statistics." Natural Areas Journal

"...it is evident that a great deal of scholarship has gone into this book and that there is much good advice in it." Ecology

"... the book is highly recommended. It provides a broad and in-depth overview over most of the commonly used statistical methods." Ethology

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Product Details

  • ISBN-13: 9781107085664
  • Publisher: Cambridge University Press
  • Publication date: 10/28/2013
  • Sold by: Barnes & Noble
  • Format: eBook
  • Edition number: 1
  • File size: 37 MB
  • Note: This product may take a few minutes to download.

Meet the Author

Gerry Quinn is a Senior Lecturer in the School of Biological Sciences at Monash University, and Program Leader in the Cooperative Research Centre for Freshwater Ecology. He has taught experimental design and analysis courses for a number of years and has provided advice on the design and analysis of sampling and experimental programs in ecology and environmental monitoring to a wide range of university and government scientists. Gerry Quinn is a co-author of Monitoring Ecological Impacts: Concepts and Practice in Flowing Waters, Cambridge University Press, 2002.

Michael Keough is a Reader in Zoology at the University of Melbourne. His research interests lie in marine ecology, environmental science, and conservation biology. He has extensive experience teaching experimental design and analysis courses at a number of universities. He has also provided advice on design and analysis for environmental monitoring to a wide range of environmental consultants, and state and federal governments in Australia. Michael Keough is a co-author of Monitoring Ecological Impacts: Concepts and Practice in Flowing Waters, Cambridge University Press, 2002.

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Table of Contents

Preface
1 Introduction 1
2 Estimation 14
3 Hypothesis testing 32
4 Graphical exploration of data 58
5 Correlation and regression 72
6 Multiple and complex regression 111
7 Design and power analysis 155
8 Comparing groups or treatments - analysis of variance 173
9 Multifactor analysis of variance 208
10 Randomized blocks and simple repeated measures: unreplicated two factor designs 262
11 Split-plot and repeated measures designs: partly nested analyses of variance 301
12 Analyses of covariance 339
13 Generalized linear models and logistic regression 359
14 Analyzing frequencies 380
15 Introduction to multivariate analyses 401
16 Multivariate analysis of variance and discriminant analysis 425
17 Principal components and correspondence analysis 443
18 Multidimensional scaling and cluster analysis 473
19 Presentation of results 494
References 511
Index 527
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