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Statistical Modeling With R : a dual frequentist and Bayesian approach for life scientists - Pablo  Inchausti
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Statistical Modeling With R

a dual frequentist and Bayesian approach for life scientists

By: Pablo Inchausti

Hardcover | 2 November 2022

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To date, statistics has tended to be neatly divided into two theoretical approaches or frameworks: frequentist (or classical) and Bayesian. Scientists typically choose the statistical framework to analyse their data depending on the nature and complexity of the problem, and based on their personal views and prior training on probability and uncertainty. Although textbooks and courses should reflect and anticipate this dual reality, they rarely do so. This accessible textbook explains, discusses, and applies both the frequentist and Bayesian theoretical frameworks to fit the different types of statistical models that allow an analysis of the types of data most commonly gathered by life scientists. It presents the material in an informal, approachable, and progressive manner suitable for readers with only a basic knowledge of calculus and statistics.

Statistical Modeling with R is aimed at senior undergraduate and graduate students, professional researchers, and practitioners throughout the life sciences, seeking to strengthen their understanding of quantitative methods and to apply them successfully to real world scenarios, whether in the fields of ecology, evolution, environmental studies, or computational biology.
Industry Reviews
A book that should attract curious minds of various backgrounds, knowledge, and expertise in statistics, as well as work nicely to support an enthusiastic teacher of statistical modeling. I thus recommend this book most enthusiastically. * Christian P. Robert, Journal of the American Statistical Association *
The book is a novel contribution to the literature on statistical modelling, it has my highest endorsement, and I look forward to using it in future graduate courses on applied statistics. * Lars Roennegard, Dalarna University *

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