Getting Started with R : An Introduction for Biologists

R is rapidly becoming the standard computational environment for analysis, graphical presentations and programming in the biological sciences. This book details how to start doing statistics in R or how to integrate the use of R with an existing research programme and how to achieve this efficiently and reliably. 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 Getting Started with R deals with learning how to get answers from data, an integral part of modern training in the natural, physical, social, and engineering sciences. One of the most exciting developments in data management, quantitative analysis, and visualization was the growth of the open source application R. This statistics and programming language has emerged as a critical component of biologists’, and many other scientists’, toolboxes. R is rapidly becoming standard software for data manipulation, visualization, and analysis. This book provides a functional introduction for biologists new to R. While teaching how to import, visualize, and analyse, it keeps readers focused on their ultimate goals ... to communicate their data and analyses in presentations, posters, papers, websites, and reports. It provides a consistent approach and workflow for using R, one that is simple, efficient, intuitive, reliable, accurate, and reproducible. The material in the book reproduces the engaging and sometimes humorous nature of the three-day course on which it is based. What is different in the second edition? It has been entirely rewritten to accommodate several new developments in R and changes made in teaching the course. Chapters have been added on preparing data for R, on analyses of more experimental designs (regression and one-way and two-way ANOVA, in addition to the old ANCOVA example), and on generalized linear models. The book also uses as default a popular, new set of tools for managing data and producing graphs via the add-on packages dplyr and ggplot2 . There are now three authors "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."--Publisher's website Learning how to get answers from data is an integral part of modern training in the natural, physical, social, and engineering sciences. One of the most exciting changes in data management and analysis during the last decade has been the growth of open source software. The open source statistics and programming language R has emerged as a critical component of any researcher's toolbox. Indeed, R is rapidly becoming the standard software for analyses, graphical presentations, andprogramming in the biological sciences. This book provides a functional introduction for biologists new to R. While te. A popular entry-level guide into the use of R as a statistical programming and data management language for students, post-docs, and seasoned researchers now in a new revised edition, incorporating the updates in the R environment, and also adding guidance on the use of more complex statistical analyses and tools. R is rapidly becoming the standard computational environment for analysis, graphical presentations and programming in the biological sciences. This work details how to start doing statistics in R or how to integrate the use of R with an existing research programme and how to achieve this efficiently and reliably