Statistical Modeling with R: A Dual Frequentist and Bayesian Approach for Life Scientists

To date, statistics has tended to be neatly divided into two theoretical approaches or frameworks: frequentist (or...
BD$118.31 BMD
BD$118.31 BMD
SKU: 9780192859020
Product Type: Books
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Author: Pablo Inchausti
Format: Paperback
Language: English
Subtotal: BD$118.31
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Statistical Modeling with R: A Dual Frequentist and Bayesian Approach for Life Scientists by Inchausti, Pablo

Statistical Modeling with R: A Dual Frequentist and Bayesian Approach for Life Scientists

BD$118.31

Statistical Modeling with R: A Dual Frequentist and Bayesian Approach for Life Scientists

BD$118.31
Author: Pablo Inchausti
Format: Paperback
Language: English
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.


Author: Pablo Inchausti
Publisher: Oxford University Press, USA
Published: 02/02/2023
Pages: 480
Binding Type: Paperback
Weight: 2.30lbs
Size: 9.30h x 7.80w x 1.40d
ISBN: 9780192859020

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