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

Statistical Modeling with R is a textbook that explains and applies both the frequentist and Bayesian theoretical frameworks to fit statistical models for analyzing life science data. It is suitable for readers with basic knowledge of calculus and statistics and is aimed at senior undergraduate and graduate students, professional researchers, and practitioners in the life sciences.

Format: Hardback
Length: 480 pages
Publication date: 02 November 2022
Publisher: Oxford University Press

Statistics has traditionally been categorized into two theoretical approaches: frequentist (or classical) and Bayesian. Scientists often select a statistical framework to analyze their data based on the nature and complexity of the problem, as well as their personal beliefs and prior experience with probability and uncertainty. While textbooks and courses should acknowledge and account for this dual reality, they often fail to do so. This accessible textbook provides an explanation, discussion, and application of both the frequentist and Bayesian theoretical frameworks to fit a range of statistical models used in analyzing the types of data commonly collected by life scientists. The material is presented in an informal, approachable, and progressive manner, suitable for readers with a basic understanding of calculus and statistics. Statistical Modeling with R is designed for senior undergraduate and graduate students, professional researchers, and practitioners in the life sciences, aiming to enhance their understanding of quantitative methods and apply them effectively to real-world scenarios across fields such as ecology, evolution, environmental studies, and computational biology.

Weight: 1214g
Dimension: 194 x 253 x 29 (mm)
ISBN-13: 9780192859013