Practical R for Biologists An Introduction by Donald L.J. Quicke Buntika A. Butcher Rachel A. Kruft Welton
R is a freely available, open-source statistical programming environment which provides powerful statistical analysis tools and graphics outputs. R is now used by a very wide range of people; biologists (the primary audience of this book), but also all other scientists and engineers, economists, market researchers and medical professionals. R users with expertise are constantly adding new associated packages, and the range already available is immense. This text works through a set of studies that collectively represent almost all the R operations that biology students need in order to analyse their own data. The material is designed to serve students from first year undergraduates through to those beginning post graduate levels. Chapters are organized around topics such as graphing, classical statistical tests, statistical modelling, mapping, and text parsing. Examples are based on real scientific studies, and each one covers the use of more R functions than those simply necessary to get a p-value or plot.
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Practical R for Biologists An Introduction by Donald L.J. Quicke Buntika A. Butcher Rachel A. Kruft Welton
Author: Donald L.J. Quicke Buntika A. Butcher Rachel A. Kruft Welton
R is a freely available, open-source statistical programming environment which provides powerful statistical analysis tools and graphics outputs. R is now used by a very wide range of people; biologists (the primary audience of this book), but also all other scientists and engineers, economists, market researchers and medical professionals. R users with expertise are constantly adding new associated packages, and the range already available is immense. This text works through a set of studies that collectively represent almost all the R operations that biology students need in order to analyse their own data. The material is designed to serve students from first year undergraduates through to those beginning post graduate levels. Chapters are organized around topics such as graphing, classical statistical tests, statistical modelling, mapping, and text parsing. Examples are based on real scientific studies, and each one covers the use of more R functions than those simply necessary to get a p-value or plot.
Actually super useful for biology university students who need to know R for their course. Pretty thick though I’m warning you. Still there’s basically no books that include everything you need but this one does. Eartha                                                  rated it: 5.0 from 5.0
The best book for learning R. It’s user friendly and easy to pick up with useful diagrams. Helped me through a few programming classes! Idonea Kw                                               rated it: 5.0 from 5.0
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Donald L.J. Quicke Buntika A. Butcher Rachel A. Kruft Welton
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