
R is rapidly becoming the standard software for statistical analyses, graphical presentation of data, and programming in the natural, physical, social, and engineering sciences. Getting Started with R is now the go-to introductory guide for biologists wanting to learn how to use R in their research. It teaches readers how to import, explore, graph, and analyse data, while keeping them focused on their ultimate goals: clearly communicating their data in oral presentations, posters, papers, and reports. It provides a consistent workflow for using R that is simple, efficient, reliable, and reproducible. This second edition has been updated and expanded while retaining the concise and engaging nature of its predecessor, offering an accessible and fun introduction to the packages dplyr and ggplot2 for data manipulation and graphing. It expands the set of basic statistics considered in the first edition to include new examples of a simple regression, a one-way and a two-way ANOVA. Finally, it introduces a new chapter on the generalised linear model. Getting Started with R is suitable for undergraduates, graduate students, professional researchers, and practitioners in the biological sciences.
This text investigates how biologists can effectively utilize the R programming language to perform statistical analysis, data visualization, and reproducible research. The authors, Andrew P. Beckerman, Dylan Z. Childs, and Owen L. Petchey, leverage their expertise in biological research to provide a structured workflow for data management. They argue that by mastering specific R packages and statistical models, researchers can improve the clarity and reliability of their scientific communication in academic and professional settings.
What You Will Find
Scope Limits
Experts and educators frequently cite this text as a foundational resource for students and professionals transitioning into computational biology. Readers often note the accessible prose and the practical focus on reproducible workflows as key strengths for beginners.
Page Count:
258
Publication Date:
2017-01-01
ISBN-10:
0191091936
ISBN-13:
9780191091933
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