Statistical Modeling With R: a dual frequentist and Bayesian approach for life scientistsКНИГИ » ПРОГРАММИНГ
Название: Statistical Modeling With R: a dual frequentist and Bayesian approach for life scientists Автор: Pablo Inchausti Издательство: Oxford University Press Год: 2023 Страниц: 519 Язык: английский Формат: pdf (true) Размер: 36.0 MB
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.
How is this book organized? It is unthinkable to carry out statistical analysis of meaningful amounts data of even moderate complexity without a computer. This book will make extensive use of the R programming environment. This is an open-source (one can access and edit the code of all the R functions and save a revised version in one’s computer), interpreted (it does not require compilation to be executed) programming language environment for statistical computing and graphics. R runs on Linux, Windows, and macOS, among others, and is the brainchild of its creators Ross Ihaka and Robert Gentleman. It is now supported by the R Foundation for Statistical Computing. R has experienced phenomenal growth since August 1993 to become one of the most popular and fastest growing programs for statistical analysis and graphics worldwide. Being a programming language, R can be easily extended by writing functions and extensions. There is a growing and very active R community creating packages (more than 17,500 packages) and providing answers in terms of code and explanations in many active and fast-reacting mailing lists. R code is mostly written in the R language itself, although advanced users can link it to other computer languages such as C, C++, FORTRAN, Java, and Python using specific commands to assist in the execution of computer-intensive tasks.
Most statistics books using R aim for standalone use by providing brief (and by necessity incomplete) introductory chapters about the installation and basic use of R, including the basic commands to generate graphics. The companion website contains detailed information about the installation of R in Windows, macOS, and Linux, along with the basic syntax for using and manipulating R objects. The website also provides detailed explanations for making basic plots in R using the package ggplot2, which is rapidly becoming the dominant approach to producing graphics in R.
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.
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Statistical Modeling With R: a dual frequentist and Bayesian approach for life scientists 
Название: Statistical Modeling With R: a dual frequentist and Bayesian approach for life scientists
