Introduction To Statistical Computing And Visualization Using R
Download Introduction To Statistical Computing And Visualization Using R PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Introduction To Statistical Computing And Visualization Using R book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Statistical Computing with R
Computational statistics and statistical computing are two areas that employ computational, graphical, and numerical approaches to solve statistical problems, making the versatile R language an ideal computing environment for these fields. One of the first books on these topics to feature R, Statistical Computing with R covers the traditional core material of computational statistics, with an emphasis on using the R language via an examples-based approach. Suitable for an introductory course in computational statistics or for self-study, it includes R code for all examples and R notes to help explain the R programming concepts. 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. Focusing on implementation rather than theory, this text serves as a balanced, accessible introduction to computational statistics and statistical computing.
Introduction to Statistical Computing and Visualization Using R
The book provides a foundational guide to statistical computing and visualisation Using R programming with an emphasis on practical data analysis skills that are directly applicable to diverse fields like finance, defence, health, and education. It uniquely combines a thorough explanation of basic constructs with advanced topics such as data visualisation, statistical modeling, and probability, making it accessible yet comprehensive for learners across disciplines. This approach allows readers not only to build essential R skills but also to apply them to real-world scenarios, equipping students and professionals from various disciplines with versatile analytical tools. It offers a comprehensive yet approachable introduction for students and scholars from various disciplines using R. Includes practical and interactive elements such as quizzes, coding exercises, and hands-on projects can provide an engaging and effective learning experience for readers Provides complete code solutions to every problem presented, including detailed answers to even the most complex questions Presents case studies that can help contextualize the concepts covered in the book by showing how they are used in specific industries, fields, or contexts Offers application-based practical data analysis with cases in various fields and sectors, such as finance, healthcare, and marketing Focuses on best practices and efficient coding techniques, improving productivity and maintainability of R code
Introduction to Statistical Computing and Visualization Using R
"The book provides a foundational guide to statistical computing and visualisation Using R programming with an emphasis on practical data analysis skills that are directly applicable to diverse fields like finance, defence, health, and education. It uniquely combines a thorough explanation of basic constructs with advanced topics such as data visualisation, statistical modeling, and probability, making it accessible yet comprehensive for learners across disciplines. This approach allows readers not only to build essential R skills but also to apply them to real-world scenarios, equipping students and professionals from various disciplines with versatile analytical tools. It offers a comprehensive yet approachable introduction for students and scholars from various disciplines using R. Includes practical and interactive elements such as quizzes, coding exercises, and hands-on projects can provide an engaging and effective learning experience for readers Provides complete code solutions to every problem presented, including detailed answers to even the most complex questions Presents case studies that can help contextualize the concepts covered in the book by showing how they are used in specific industries, fields, or contexts Offers application based practical data analysis with cases in various fields and sectors, such as finance, healthcare, and marketing Focuses on best practices and efficient coding techniques, improving productivity and maintainability of R code"--