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<p/><br></br><p><b> About the Book </b></p></br></br>"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"--<p/><br></br><p><b> From the Back Cover </b></p></br></br><p><b>BRIDGES THE GAP BETWEEN SAS AND R, ALLOWING USERS TRAINED IN ONE LANGUAGE TO EASILY LEARN THE OTHER</b></p> <p>SAS and R are widely-used, very different software environments. Prized for its statistical and graphical tools, R is an open-source programming language that is popular with statisticians and data miners who develop statistical software and analyze data. SAS (Statistical Analysis System) is the leading corporate software in analytics thanks to its faster data handling and smaller learning curve. SAS for R Users enables entry-level data scientists to take advantage of the best aspects of both tools by providing a cross-functional framework for users who already know R but may need to work with SAS.</p> <p>Those with knowledge of both R and SAS are of far greater value to employers, particularly in corporate settings. Using a clear, step-by-step approach, this book presents an analytics workflow that mirrors that of the everyday data scientist. This up-to-date guide is compatible with the latest R packages as well as SAS University Edition. Useful for anyone seeking employment in data science, this book: </p> <ul> <li>Instructs both practitioners and students fluent in one language seeking to learn the other</li> <li>Provides command-by-command translations of R to SAS and SAS to R</li> <li>Offers examples and applications in both R and SAS</li> <li>Presents step-by-step guidance on workflows, color illustrations, sample code, chapter quizzes, and more</li> <li>Includes sections on advanced methods and applications</li> </ul> <p>Designed for professionals, researchers, and students, <i>SAS for R Users</i> is a valuable resource for those with some knowledge of coding and basic statistics who wish to enter the realm of data science and business analytics.</p><p/><br></br><p><b> About the Author </b></p></br></br><p><b>AJAY OHRI </b>is the founder of analytics startup Decisionstats.com. His research interests include spreading open source analytics, analyzing social media manipulation with mechanism design, simpler interfaces to cloud computing, investigating climate change, and knowledge flows. He currently advises startups in analytics off shoring, analytics services, and analytics. He is the author of <i>Python for R Users: A Data Science Approach</i> (Wiley), <i>R for Business Analytics</i>, and <i>R for Cloud Computing</i>.</p>

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