Scholay

学术搜索 · AI 审稿 · LaTeX 协作

Experimental Design and Data Analysis for Biologists

作者:Gerry P. Quinn, Michael J. Keough · 发表于:Cambridge University Press eBooks · 年份:2023 · DOI:10.1017/9781139568173 · 被引用次数:457 · 研究领域:Genetics, Bioinformatics, and Biomedical Research

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.