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Data Analysis for the Life Sciences with R - Rafael A. Irizarry

Data Analysis for the Life Sciences with R

By: Rafael A. Irizarry

Hardcover | 27 July 2017 | Edition Number 1

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This textbook presents modern algebra from the ground up using numbers and symmetry. The idea of a ring and of a field are introduced in the context of concrete number systems. Groups arise from considering transformations of simple geometric objects. The analysis of symmetry provides the student with a visual introduction to the central algebraic notion of isomorphism.
Designed for a typical one-semester undergraduate course in modern algebra, it provides a gentle introduction to the subject by allowing students to see the ideas at work in accessible examples, rather than plunging them immediately into a sea of formalism. The student is involved at once with interesting algebraic structures, such as the Gaussian integers and the various rings of integers modulo n, and is encouraged to take the time to explore and become familiar with those structures.
In terms of classical algebraic structures, the text divides roughly into three parts:
Industry Reviews

"In addition to the presentation of several strategies designed to handle multivariate data, the book's strength lies in its immediate applicability. By including relevant datasets, the embedding of R code throughout, and in the open source nature of its production (it was written in R markdown), the book has encouraged reproducible research while connecting computer code to the relevant statistical concepts. Practitioners in the life sciences would seemingly be well served to use the book as a guide for their research. . .. The open-source nature of the book is a unique benefit, as it ensures that future versions can swiftly update to include new concepts, data, or coding techniques. . . The book could also function as a textbook, particularly for a course in computational biology (either advanced undergraduate or introductory graduate).
~The American Statistician, Reviews of Books and Teaching Materials

"Overall, I found that this book is excellent for researchers in the life sciences who are interested in retrieving, analyzing, and interpreting complex research data using sophisticated statistical methods and computing. The authors have effectively condensed broad and important topics into a single book. I highly recommend this book to anyone venturing into the exciting world of data analysis in many areas."
~ Biometrics

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