Experimental Design and Data Analysis for Biologists by Gerry P. Quinn Paperback

Description: FREE SHIPPING UK WIDE Experimental Design and Data Analysis for Biologists by Gerry P. Quinn, Michael J. Keough Requiring only introductory statistics and basic mathematics, this textbook avoids jargon and provides worked examples, data sets and R code, and review exercises. Designed for advanced undergraduates and postgraduates studying biostatistics and experiment design in biology-related fields, it applies statistical concepts to biological scenarios. FORMAT Paperback CONDITION Brand New Publisher Description Applying statistical concepts to biological scenarios, this established textbook continues to be the go-to tool for advanced undergraduates and postgraduates studying biostatistics or experimental design in biology-related areas. Chapters cover linear models, common regression and ANOVA methods, mixed effects models, model selection, and multivariate methods used by biologists, requiring only introductory statistics and basic mathematics. Demystifying statistical concepts with clear, jargon-free explanations, this new edition takes a holistic approach to help students understand the relationship between statistics and experimental design. Each chapter contains further-reading recommendations, and worked examples from todays biological literature. All examples reflect modern settings, methodology and equipment, representing a wide range of biological research areas. These are supported by hands-on online resources including real-world data sets, full R code to help repeat analyses for all worked examples, and additional review questions and exercises for each chapter. Author Biography Gerry Quinn is an Honorary Professor in the School of Life and Environmental Sciences at Deakin University, having served as Chair in Marine Biology and Head of Warrnambool Campus during his academic career. He has extensive experience in teaching biostatistics at Deakin University and the University of Gothenburg. Michael J. Keough is an ecologist, environmental scientist, and honorary Professor in the School of Biosciences at University of Melbourne. Table of Contents Contents: List of Acronyms; Preface; 1. Introduction; 2. Things to Know Before Proceeding; 3. Sampling and Experimental Design; 4. Introduction to Linear Models; 5. Exploratory Data Analysis; 6. Simple Linear Models with One Predictor; 7. Linear Models for Crossed (Factorial) Designs; 8. Multiple Regression Models; 9. Predictor Importance and Model Selection in Multiple Regression Models; 10. Random Factors in Factorial and Nested Designs; 11. Split-plot (Split-unit) Designs: Partly Nested Models; 12. Repeated Measures Designs; 13. Generalized Linear Models for Categorical Responses; 14. Introduction to Multivariate Analyses; 15. Multivariate Analyses Based on Eigenanalyses; 16. Multivariate Analyses Based on (dis)similarities or Distances; 17. Telling Stories with Data; References; Glossary; Index. Review The new edition of this go-to text, has been revised to take a more holistic, informative, and up-to-date approach to the subject. This remarkably accessible, practical and - at times - entertaining guide to how we can best translate our questions and ideas into informative experiments and analyses is highly recommended for everyone wanting to investigate, visualise, and analyse biological phenomena. Jonathon Havenhand, University of GothenburgThe new book is an excellent resource for researchers, analysts and teachers. The text clearly outlines the important concepts of the tests and models. The examples are all based on published data which makes it easy to source the full manuscript, datasets and replicate the analyses which is incredibly important and assists with interpretation. Victoria Goodall, VLG Statistical ServicesAt last, a book for undergraduates and graduates that distills the complexities of biological data analysis into an easy-to-understand generalized linear model approach - with examples in R! The authors challenge the reader to think critically about data by providing important details on design, summary statistics, power analysis/effect size, model fit, and data visualization. This book will be used in my classes for years to come. Greg Moyer, Mansfield UniversityI have been using Experimental Design and Data Analysis for teaching and research for 20 years and have been hoping for a second edition for 10. It was worth the wait. The new edition shares many attributes with the original. It is quite easy to read, the examples are varied and interesting, there are ample and revealing box examples and there remains an attitude of Statistics as a tool that will be used by many. There are a number of changes that reflect these attributes - two key ones are the emphasis on Generalized Models as a framework for a broad array of approaches and the conversion of examples to R, with code and additional material available online. Peter Raimondi, University of California, Santa CruzI have taught in and coordinated a third-year design/statistics paper for zoology and ecology students for ten years - an enjoyable and sometimes challenging task. The first edition of Quinn and Keough has been immensely helpful for me in teaching this course. The second edition has been updated and expanded considerably. Im sure it will continue to inspire my future teaching. Christoph Matthaei, University of OtagoI was excited to see Quinn and Keough have updated their classic guide to experimental design and data analysis. I read the earlier edition of this book as a graduate student, and the advice it provides on experimental design is the foundation of my own studies, as well as my approach to training graduate students … This book is foundational reading for aspiring scientists. Not only does it teach you how to analyse your data, it also provides invaluable advice on how to communicate analyses and write up scientific studies. The books advice will help give early career scientists the confidence they need to write-up and publish their first studies. Chris Brown, University of Tasmania Promotional A biostatistics textbook for upper undergraduate and graduate students, covering analyses used by biologists and now including R code. Details ISBN1107687675 Author Michael J. Keough Pages 405 Publisher Cambridge University Press Year 2023 Edition 2nd ISBN-13 9781107687677 Format Paperback Imprint Cambridge University Press Place of Publication Cambridge Country of Publication United Kingdom AU Release Date 2023-09-30 NZ Release Date 2023-09-30 Illustrations 140 Halftones, black and white ISBN-10 1107687675 Edition Description 2nd Revised edition Replaces 9780521009768 Audience General DEWEY 570.724 Publication Date 2023-09-07 UK Release Date 2023-09-07 Alternative 9781139568173 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! 30 DAY RETURN POLICY No questions asked, 30 day returns! FREE DELIVERY No matter where you are in the UK, delivery is free. SECURE PAYMENT Peace of mind by paying through PayPal and eBay Buyer Protection TheNile_Item_ID:143299995;

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