Better framing in intro

rmarkdown.Rmd

@@ -2,19 +2,22 @@
 
 ## Introduction
 
-R Markdown provides an unified authoring framework for data science, combining your code, its results, and your prose commentary. R Markdown documents are fully reproducible and support dozens of output formats, like PDFs, Word files, slideshows, and more. RMarkdown files are designed to be used in two ways:
+R Markdown provides an unified authoring framework for data science, combining your code, its results, and your commentary in prose. R Markdown documents are fully reproducible and support dozens of output formats, like PDFs, Word files, slideshows, and more. 
 
-You can use R Markdown in notebook mode for 
-  analyst-to-analyst communication, and in report mode for 
-  analyst-to-decision-maker communication. Thanks to the power of R Markdown
-  formats, you can even use the same document for both purposes.
+R Markdown files are designed to be used in three ways:
 
-1.  To produce a final report that you can share with others.
+1.  For communicating to decision makers, who want to focus on the conclusions,
+    not the code behind the analysis.
 
-1.  As a notebook, which allows yout to mingle prose, code, and output during 
-    your own analyses.
+1.  For collaborating with other data scientists (including future you!), who
+    are interested in both your conclusions, and how you reached them (i.e
+    the code).
+    
+1.  As an environment in which to _do_ data science, as a modern day lab 
+    notebook where you can capture not only what you did, but also what you
+    were thinking.
 
-The name R Markdown is slightly misleading because you can use it with other languages, not just R. R Markdown has recently added support for Python and SQL, and that support will improve over time. To use a different language in code chunk, just replace the `r` in  ```` ```{r} ```` with `python` or `sql`. We'll focus on R here, for obvious reasons!
+Thanks to the design of R Markdown, you can use one file to achieve all of these goals simultaneously.
 
 R Markdown integrates a number of R packages and external tools. This means that helps is, by-and-large, not available through `?`. Instead, as you work through chapter, and use R Markdown in the future, keep these resouces close to hand:
 
@@ -288,9 +291,6 @@ cat(htmltools::includeText("rmarkdown-demos/1-example.Rmd"))
 knitr::include_graphics("images/inline-1-heat.png")
 ```
 
-```{r, echo = FALSE, out.width = "100%"}
-```
-
 Inline expressions do not take knitr options. When processing inline code, R Markdown will always display the results of inline code, so that inline output is indistinguishable from the surrounding text. 
 
 ## YAML header
@@ -381,6 +381,8 @@ As with the bibliography field, your csl file should contain a path to the file.
 
 ## Learning more
 
+R Markdown is still relatively young, and is still growing rapidly. The best place to stay on top of innovations is the official R Markdown website: <http://rmarkdown.rstudio.com>.
+
 There are two important topics that we haven't covered here: collaboration, and the details of accurately communicating your ideas to other humans. Collaboration is a vital part of modern data science, and you can make your life much easier by using version control tools, such as Git and Github. We recommend two free resources that will teach you about Git:
 
 1.  "Happy Git with R": a user friendly introduction to Git and GitHub from