Biological Data Analysis Using R
β Scribed by Dyer R.J.
- Tongue
- English
- Leaves
- 226
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
225 pages
This manuscript has been partitioned into four separate sections. The first section introduces R as a language and a tool and covers some basic topics that are required to get one going. The next section contains eleven chapters that target some particular aspect of biological inquiry from the perspective of the kind of data that will be analyzed. The third section focuses on how you can extend the R environment developing scripts and defining your own functions and libraries. The final section of this text is an appendix that includes the answers to odd-numbered questions from the exercises in each chapter as well as some additional information on installing additional libraries or groups of libraries.
There are some common elements to each chapter that make it easy for the reader to get the larger picture of the topics being introduced. At the beginning of each chapter, a specific list of topics and skills that are to be covered provided. As topics are introduced, the R code is provided and keywords from the R programming language are highlighted to help the reader follow along.
At the end of each chapter all the R functions that were used in the chapter as well as a brief definition of the arguments passed to each function is provided as a quick reference source. Each chapter also contains a set of exercises that can test the readers understanding of chapter topics. Answers to odd numbered exercise problems are provided in Appendix A. Throughout the text, all of the R functions used are also indexed so that the reader can easily find instances where they were used.
β¦ Subjects
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R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsenβs extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introd
<p>This text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. This second edition has been revised to be current with the versions of R software released since the bookβs original publication. It features updated terminology, sources, and examples thro
<p>Drawing on Gregg Hartvigsenβs extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences.</p>
<p>This text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. This second edition has been revised to be current with the versions of R software released since the bookβs original publication. It features updated terminology, sources, and examples thro
<P>R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen's extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented int