A Primer in Biological Data Analysis and Visualization Using R
β Scribed by Gregg Hartvigsen
- Publisher
- Columbia University Press
- Year
- 2014
- Tongue
- English
- Leaves
- 248
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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 introduction to R for students in the life sciences.
Underscoring the importance of R and RStudio in organizing, computing, and visualizing biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types. He covers testing data for normality, defining and identifying outliers, and working with non-normal data. Students are introduced to common one- and two-sample tests as well as one- and two-way analysis of variance (ANOVA), correlation, and linear and nonlinear regression analyses. This volume also includes a section on advanced procedures and a chapter introducing algorithms and the art of programming using R.
β¦ Subjects
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π SIMILAR VOLUMES
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
225 pages<br/>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