Foundational and Applied Statistics for Biologists Using R

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A01=Ken A. Aho
advanced biostatistics applications
Author_Ken A. Aho
biological data analysis
Category=PBT
Category=PS
eq_bestseller
eq_isMigrated=1
eq_nobargain
eq_non-fiction
eq_science
experimental statistics
hypothesis testing methods
probability theory
sampling techniques
statistical pedagogy

Product details

  • ISBN 9781032477411
  • Weight: 1440g
  • Dimensions: 178 x 254mm
  • Publication Date: 21 Jan 2023
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Full of biological applications, exercises, and interactive graphical examples, Foundational and Applied Statistics for Biologists Using R presents comprehensive coverage of both modern analytical methods and statistical foundations. The author harnesses the inherent properties of the R environment to enable students to examine the code of complicated procedures step by step and thus better understand the process of obtaining analysis results. The graphical capabilities of R are used to provide interactive demonstrations of simple to complex statistical concepts.

Assuming only familiarity with algebra and general calculus, the text offers a flexible structure for both introductory and graduate-level biostatistics courses. The first seven chapters address fundamental topics in statistics, such as the philosophy of science, probability, estimation, hypothesis testing, sampling, and experimental design. The remaining four chapters focus on applications involving correlation, regression, ANOVA, and tabular analyses.

Unlike classic biometric texts, this book provides students with an understanding of the underlying statistics involved in the analysis of biological applications. In particular, it shows how a solid statistical foundation leads to the correct application of procedures, a clear understanding of analyses, and valid inferences concerning biological phenomena.

Web ResourceAn R package (asbio) developed by the author is available from CRAN. Accessible to those without prior command-line interface experience, this companion library contains hundreds of functions for statistical pedagogy and biological research. The author’s website also includes an overview of R for novices.

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