Includes bibliographical references and index.

About SAS and R -- Data input, import and print -- Data inspection and cleaning -- Handling dates, strings, numbers -- Numerical summary and group by analysis -- Frequency distributions and cross tabulations -- Using SQL with SAS and R -- Functions, loops, arrays, macros -- Data visualization -- Data output -- Statistics for data scientists.

"This book will enable students and practitioners to easily switch from R to SAS and vice versa. R has better statistical and graphical tools, while SAS has faster data handling, is easier to learn and is the leading corporate software in analytics. This book builds a cross-functional framework for students who already know R but may need to work on SAS language in corporate environments. Using a simple how-to-do-it in a step-by-step way approach, the book presents an analytics workflow similar to those used by the everyday data scientist. The book is designed to be compatible with the latest R packages as well as SAS University Edition. It also includes advanced section for the reader who wishes to get a greater understanding of more advanced methods. The book will be useful to students, researchers, and practitioners globally as well as anyone looking to get a job in data science today"-- Provided by publisher.

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