{"product_id":"statistical-computing-with-r-second-edition-hardcover","title":"Statistical Computing with R, Second Edition - Hardcover","description":"\u003cp\u003eby \u003cb\u003eMaria L. Rizzo\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003ePraise for the First Edition: \u003c\/p\u003e\u003cp\u003e\". . . the book serves as an excellent tutorial on the R language, providing examples that illustrate programming concepts in the context of practical computational problems. The book will be of great interest for all specialists working on computational statistics and Monte Carlo methods for modeling and simulation.\" - Tzvetan Semerdjiev, \u003ci\u003eZentralblatt Math\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003eComputational statistics and statistical computing are two areas within statistics that may be broadly described as computational, graphical, and numerical approaches to solving statistical problems. Like its bestselling predecessor, \u003cb\u003e\u003ci\u003eStatistical Computing with R, Second Edition\u003c\/i\u003e\u003c\/b\u003e covers the traditional core material of these areas with an emphasis on using the R language via an examples-based approach. The new edition is up-to-date with the many advances that have been made in recent years. \u003c\/p\u003e\u003cp\u003eFeatures\u003c\/p\u003e\u003cul\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eProvides an overview of computational statistics and an introduction to the R computing environment.\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eFocuses on implementation rather than theory.\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eExplores key topics in statistical computing including Monte Carlo methods in inference, bootstrap and jackknife, permutation tests, Markov chain Monte Carlo (MCMC) methods, and density estimation.\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eIncludes new sections, exercises and applications as well as new chapters on resampling methods and programming topics.\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eIncludes coverage of recent advances including R Studio, the tidyverse, knitr and ggplot2\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eAccompanied by online supplements available on GitHub including R code for all the exercises as well as tutorials and extended examples on selected topics.\u003c\/li\u003e \u003c\/ul\u003e\u003cp\u003eSuitable for an introductory course in computational statistics or for self-study, \u003cb\u003e\u003ci\u003eStatistical Computing with R\u003c\/i\u003e\u003c\/b\u003e, Second Edition provides a balanced, accessible introduction to computational statistics and statistical computing.\u003c\/p\u003e\u003cp\u003eAbout the Author\u003c\/p\u003e\u003cp\u003eMaria Rizzo is Professor in the Department of Mathematics and Statistics at Bowling Green State University in Bowling Green, Ohio, where she teaches statistics, actuarial science, computational statistics, statistical programming and data science. Prior to joining the faculty at BGSU in 2006, she was Assistant Professor in the Department of Mathematics at Ohio University in Athens, Ohio. Her main research area is energy statistics and distance correlation. She is the software developer and maintainer of the energy package for R. She also enjoys writing books including a forthcoming joint research monograph on energy statistics. \u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eMaria Rizzo\u003c\/strong\u003e is Professor in the Department of Mathematics and Statistics at Bowling Green State University in Bowling Green, Ohio, where she teaches statistics, actuarial science, computational statistics, statistical programming and data science. Prior to joining the faculty at BGSU in 2006, she was Assistant Professor in the Department of Mathematics at Ohio University in Athens, Ohio. Her main research area is energy statistics and distance correlation. She is the software developer and maintainer of the energy package for R. She also enjoys writing books including a forthcoming joint research monograph on energy statistics. \u003c\/p\u003e\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 490\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1.2 x 9.3 x 6.3 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e March 06, 2019\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":42733995491391,"sku":"9781466553323","price":235.2,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0105\/8226\/1823\/files\/a3bfbf3ec43b37da6e4dba51359fbead.webp?v=1765138258","url":"https:\/\/dhlswag.com\/products\/statistical-computing-with-r-second-edition-hardcover","provider":"BBB","version":"1.0","type":"link"}