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Biostatistics With R by Jan Leps
£28.99
Available
Product Ref. (e.g. ISBN, SKU)
9781108727341
Published:
30 Jul 2020
Format:
Paperback
Number of pages:
382 pages
Dimensions:
245x173x19mm
Weight:
0.770kgs
Author:
A straightforward introduction on how to analyse data from the field of biological research and conservation. All chapters are supplemented by thoroughly explained R code demonstrating interpretation of the results. An ideal reference for students, researchers and professionals, as well as lecturers of undergraduate courses.
Biostatistics with R provides a straightforward introduction on how to analyse data from the wide field of biological research, including nature protection and global change monitoring. The book is centred around traditional statistical approaches, focusing on those prevailing in research publications. The authors cover t-tests, ANOVA and regression models, but also the advanced methods of generalised linear models and classification and regression trees. Chapters usually start with several useful case examples, describing the structure of typical datasets and proposing research-related questions. All chapters are supplemented by example datasets, step-by-step R code demonstrating analytical procedures and interpretation of results. The authors also provide examples of how to appropriately describe statistical procedures and results of analyses in research papers. This accessible textbook will serve a broad audience, from students, researchers or professionals looking to improve their everyday statistical practice, to lecturers of introductory undergraduate courses. Additional resources are provided on www.cambridge.org/biostatistics.
About the Author: Jan Lepš is Professor of Ecology in the Department of Botany, Faculty of Science, University of South Bohemia, Ceské Budejovice, Czech Republic. His main research interests include plant functional ecology, particularly the mechanisms of species coexistence and stability, and ecological data analysis. He has taught many ecological and statistical courses and supervised more than 80 student theses, from undergraduate to PhD.
| Number of pages | 382 |
|---|
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