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Author Holmes, Susan, 1954- author.

Title Modern statistics for modern biology / Susan Holmes, Stanford University, California, Wolfgang Huber, European Molecular Biology Laboratory.

Publication Info. Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2019.
©2019

Copies

Location Call No. OPAC Message Status
 Axe 2nd Floor Stacks  570.15195 H738m 2019    ---  Available
1 copy being processed for Axe Acquisitions Order.
Description xxiii, 382 pages : illustrations (some color) ; 28 x 22 cm
text txt rdacontent
still image sti rdacontent
unmediated n rdamedia
volume nc rdacarrier
Bibliography Includes bibliographical references (pages 367-376) and index.
Contents Generative models for discrete data -- Statistical modeling -- High-quality graphics in R -- Mixture models -- Clustering -- Testing -- Multivariate analysis -- High-throughput count data -- Multivariate methods for heterogeneous data -- Networks and trees -- Image data -- Supervised learning -- Design of high-throughput experiments and their analyses.
Summary "If you are a biologist and want to get the best out of the powerful methods of modern computational statistics, this is your book. You can visualize and analyze your own data, apply unsupervised and supervised learning, integrate datasets, apply hypothesis testing, and make publication-quality figures using the power of R/Bioconductor and ggplot2. This book will teach you "cooking from scratch," from raw data to beautiful illuminating output, as you learn to write your own scripts in the R language and to use advanced statistics packages from CRAN and Bioconductor."--back cover
Subject Biometry.
Biomathematics.
Science.
Biomathematics. (OCoLC)fst00832555
Biometry. (OCoLC)fst00832611
Added Author Huber, Wolfgang, author.
ISBN 1108705294 paperback
9781108705295 paperback
9781108427029 hardback
Standard No. 10.1017/9781108551441 doi

 
    
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