R Recipes is your handy problem-solution reference for learning and using the popular R programming language for statistics and other numerical analysis. Packed with hundreds of code and visual recipes, this book helps you to quickly learn the fundamentals and explore the frontiers of programming, analyzing and using R. R Recipes provides textual and visual recipes for easy and productive templates for use and re-use in your day-to-day R programming and data analysis practice. Whether you're in finance, cloud computing, big or small data analytics, or other applied computational and data science - R Recipes should be a staple for your code reference library.
Beginning R, Second Edition has been updated to cover R version 3.0 or latest iteration of it. It is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. This book shows the use of R in specific use cases such as simulations, discrete probability solutions, one-way ANOVA analysis, and more. It takes a hands-on, example-based approach incorporating best practices with clear explanations of the statistics being done. R is a powerful open-source implementation of the statistical language S, which was developed by AT&T. R has eclipsed S and the commercially-available S-Plus language, and has become the de facto standard for doing, teaching, and learning computational statistics. R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets. R is also becoming adopted into commercial tools such as Oracle Database. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for statistical exploration and research.
The book offers a practical guide to mastering the R programming language, emphasizing its utility in statistical programming. It covers essential skills such as writing and saving scripts, building data files, and creating custom statistical functions. With a focus on hands-on learning, it explores various applications of R, including simulations and multivariate analysis, while providing clear explanations of statistical concepts. The growing popularity and community support for R make it a valuable tool for anyone interested in computational statistics and research.
Beginning R, Second Edition is a hands-on book showing how to use the R language, write and save R scripts, read in data files, and write custom statistical functions as well as use built in functions. This book shows the use of R in specific cases such as one-way ANOVA analysis, linear and logistic regression, data visualization, parallel processing, bootstrapping, and more. It takes a hands-on, example-based approach incorporating best practices with clear explanations of the statistics being done. It has been completely re-written since the first edition to make use of the latest packages and features in R version 3. R is a powerful open-source language and programming environment for statistics and has become the de facto standard for doing, teaching, and learning computational statistics. R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets, with a constantly evolving ecosystem of packages providing new functionality for data analysis. R has also become popular in commercial use at companies such as Microsoft, Google, and Oracle. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for data analysis and research. What You Will Learn: How to acquire and install R Hot to import and export data and scripts How to analyze data and generate graphics How to program in R to write custom functions Hot to use R for interactive statistical explorations How to conduct bootstrapping and other advanced techniques
