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After an overview of computational statistics and an introduction to the R computing environment, the book reviews some basic concepts in probability and classical statistical inference. Each subsequent chapter explores a specific topic in computational statistics. These chapters cover the simulation of random variables from probability distributions, the visualization of multivariate data, Monte Carlo integration and variance reduction methods, Monte Carlo methods in inference, bootstrap and jackknife, permutation tests, Markov chain Monte Carlo (MCMC) methods, and density estimation. The final chapter presents a selection of examples that illustrate the application of numerical methods using R functions.      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With straightforward examples, the book takes you through a reproducible research workflow, showing you how to use:         R for dynamic data gathering and automated results presentation  knitr for combining statistical analysis and results into one document LaTeX for creating PDF articles and slide shows, and Markdown and HTML for presenting results on the web  Cloud storage and versioning services that can store data, code, and presentation files; save previous versions of the files; and make the information widely available  Unix-like shell programs for compiling large projects and converting documents from one markup language to another RStudio to tightly integrate reproducible research tools in one place         Whether you’re an advanced user or just getting started with tools such as R and LaTeX, this book saves you time searching for information and helps you successfully carry out computational research. 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Supplementary files used for the examples and a reproducible research project are available on the author’s website.","brand":"WoB","offers":[{"title":"US \/ GOOD \/ SBYB","offer_id":50131670171921,"sku":"CIN1466572841G","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"US \/ VERY_GOOD \/ SBYB","offer_id":50384468017425,"sku":"CIN1466572841VG","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ VERY_GOOD \/ INTERNAL","offer_id":52108957679889,"sku":"GOR009002483","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1466572841.jpg?v=1750758064"},{"product_id":"essentials-of-data-science-knowledge-discovery-using-r-book-graham-j-williams-9781138088634","title":"The Essentials of Data Science: Knowledge Discovery Using R","description":"The Essentials of Data Science: Knowledge Discovery Using R presents the concepts of data science through a hands-on approach using free and open source software. It systematically drives an accessible journey through data analysis and machine learning to discover and share knowledge from data.  Building on over thirty years’ experience in teaching and practising data science, the author encourages a programming-by-example approach to ensure students and practitioners attune to the practise of data science while building their data skills. Proven frameworks are provided as reusable templates. Real world case studies then provide insight for the data scientist to swiftly adapt the templates to new tasks and datasets.       The book begins by introducing data science. It then reviews R’s capabilities for analysing data by writing computer programs. These programs are developed and explained step by step. From analysing and visualising data, the framework moves on to tried and tested machine learning techniques for predictive modelling and knowledge discovery. Literate programming and a consistent style are a focus throughout the book.","brand":"WoB","offers":[{"title":"US \/ VERY_GOOD \/ SBYB","offer_id":50372598563089,"sku":"CIN1138088633VG","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ VERY_GOOD \/ INTERNAL","offer_id":52634255196433,"sku":"GOR014572278","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1138088633.jpg?v=1750709187"},{"product_id":"dynamic-documents-with-r-and-knitr-book-yihui-xie-9781482203530","title":"Dynamic Documents with R and knitr","description":"The cut-and-paste approach to writing statistical reports is not only tedious and laborious, but also can be harmful to scientific research, because it is inconvenient to reproduce the results. Dynamic Documents with R and knitr introduces a new approach via dynamic documents, i.e. integrating computing directly with reporting. A comprehensive guide to the R package knitr, the book covers examples, document editors, basic usage, detailed explanations of a wide range of options, tricks and solutions, extensions, and complete applications of this package.   The book provides an overview of dynamic documents, introducing the idea of literate programming. It then explains the importance of dynamic documents to scientific research and its impact on reproducible research. Building on this, the author covers basic concepts, common text editors that support knitr, and the syntax for different document formats such as LaTeX, HTML, and Markdown before going on to discuss core functionality, how to control text and graphics output, caching mechanisms that can reduce computation time, and reuse of source code. He then explores advanced topics such as chunk hooks, integrating other languages such as Python and awk into one report in the knitr framework, and useful tricks that make it easier to write documents with knitr. Discussions of how to publish reports in a variety of formats, applications, and other tools complete the coverage.   Suitable for both beginners and advanced users, this book shows you how to write reports in simple languages such as Markdown. The reports range from homework, projects, exams, books, blogs, and web pages to any documents related to statistical graphics, computing, and data analysis. While familiarity with LaTeX and HTML is helpful, the book requires no prior experience with advanced programs or languages. For beginners, the text provides enough features to get started on basic applications. 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This combination of freely available code and data enables you to practice with the methods and modify the code to suit your own needs.","brand":"WoB","offers":[{"title":"US \/ VERY_GOOD \/ SBYB","offer_id":50384432857361,"sku":"CIN1466565209VG","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1466565209.jpg?v=1751305799"},{"product_id":"analyzing-baseball-data-with-r-book-max-marchi-9781466570221","title":"Analyzing Baseball Data with R","description":"With its flexible capabilities and open-source platform, R has become a major tool for analyzing detailed, high-quality baseball data. Analyzing Baseball Data with R provides an introduction to R for sabermetricians, baseball enthusiasts, and students interested in exploring the rich sources of baseball data. 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All of the datasets and R code used in the text are available online.      This book helps readers answer questions about baseball teams, players, and strategy using large, publically available datasets. It offers detailed instructions on downloading the datasets and putting them into formats that simplify data exploration and analysis. 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