دانلود کتاب R -اولین دوره در برنامه‌نویسی و آمار

It is entirely unsurprising that since the first edition of this book was published, R has continued to both (a) evolve as a language and (b) gain even greater popularity in science and industry. A straightforward marker of this is in the number of contributed software packages of statistical methodology and other functionality available to users (see Section A.2), which has gone from approximately 7,000 at the time of the first edition to now well over 21,000 (see https://cran.rproject. org/web/packages/). This growth in use and functionality, alongside changes to aspects of base behavior and syntax of the language, necessitates keeping introductory texts and tutorials up-to-date and hence forms the motivation for the second edition of The Book of R: A First Course in Programming and Statistics. The broad aims of this edition mirror those I discussed in the preface to the first edition. This second edition contains a wealth of new content and topics, expands upon those originally discussed, and includes dozens of new examples and exercises. In addition, a host of other improvements, updates, and corrections are the result of a complete refresh of the preexisting content designed to reflect the latest versions of R and its packages. I’ve been pleasantly surprised by the many readers from various backgrounds who have said they’ve enjoyed The Book of R over the years via personal emails containing feedback, suggestions, questions, and errata. This engagement has been a key motivator for this refreshed edition. The rise of artificial intelligence (AI) has brought about the convenience of tools that can rapidly regurgitate code on request, though this convenience comes at the expense of one’s deeper understanding and hence hinders one’s ability to apply skills more broadly. To that end, I have tried hard to ensure that this new edition continues to provide a robust, lesson-driven utility for researchers, data scientists, students, academics, and teachers—indeed, anyone wanting to learn about the wonderful flexibility R offers with respect to manipulating, summarizing, visualizing, modeling, and ultimately understanding data.