Data analysts tend to write a lot of reports, describing their analyses and results, for their collaborators or to document their work for future reference. When we first start out, we often write an R script with all of the work, and would just send emails to collaborators, describing the results and attaching various graphs. In discussing the results, there often can be confusion about which graph was which. Moving to writing formal reports, with Word or LaTeX, there is still much time spent on getting the figures to look right. Mostly, the concern is about page breaks and generating reproducible results. Imagine the work that has to be done to find the right analysis code to fix a problem in a report generated 4 years ago on an old data set, that you hope you can still find. Ideally, such analysis reports are reproducible documents: If an error is discovered, or if some additional subjects are added to the data, you can just re-compile the report and get the new or corrected results (versus having to reconstruct figures, paste them into a Word document, and further hand-edit various detailed results). This workshop will walk you through a key package in R called knitr, that is the leading solution to these types of reports. It allows you to create a document that is a mixture of text and chunks of code. When the document is processed by knitr, chunks of code will be executed, and graphs or other results inserted into a professional looking final document. Reports can be created in many formats such as Word, PDF or as HTML webpages, and are highly customizable.