Experimental Design and Data Analysis for Biologists

Häftad, Engelska, 2023

AvGerry P. Quinn,Michael J. Keough,Victoria) Quinn, Gerry P. (Deakin University,Michael J. (University of Melbourne) Keough,Gerry P Quinn,Michael J Keough

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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 today's 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.

Produktinformation

Utgivningsdatum2023-09-07
Mått204 x 255 x 19 mm
Vikt980 g
FormatHäftad
SpråkEngelska
Antal sidor405
Upplaga2
FörlagCambridge University Press
ISBN9781107687677

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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.

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.

'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 Gothenburg