The cut-and-paste approach to writing statistical reports is not only tedious and laborious, but also can be harmful to scientific research, because it is inconvenient to reproduce the results. Dynamic Documents with R and knitr introduces a new approach via dynamic documents, i.e. integrating computing directly with reporting. A comprehensive guide to the R package knitr, the book covers examples, document editors, basic usage, detailed explanations of a wide range of options, tricks and solutions, extensions, and complete applications of this package. The book provides an overview of dynamic documents, introducing the idea of literate programming. It then explains the importance of dynamic documents to scientific research and its impact on reproducible research. Building on this, the author covers basic concepts, common text editors that support knitr, and the syntax for different document formats such as LaTeX, HTML, and Markdown before going on to discuss core functionality, how to control text and graphics output, caching mechanisms that can reduce computation time, and reuse of source code. He then explores advanced topics such as chunk hooks, integrating other languages such as Python and awk into one report in the knitr framework, and useful tricks that make it easier to write documents with knitr. Discussions of how to publish reports in a variety of formats, applications, and other tools complete the coverage.