Merge pull request #185 from jdblischak/writing-r-lessons

        some code

        ~~~

## Writing Lessons with R Markdown

Lessons can be written in R Markdown and converted to Markdown. The

main advantages of maintaining lessons in an executable format is 1)

not having to copy-paste the output and 2) it is easier to test if

new changes break code in other parts of the lesson. The main

disadvantage is that there will be more noise when merging the

generated content (e.g. different R versions have slightly different

wording of error messages).

After writing or editing a lesson written in R Markdown, automatically

generate the Markdown and html versions by running the command `make

preview`. This first runs the `knit` command from the [knitr][]

package to convert to Markdown, and then pandoc to convert to html.

[knitr]: http://yihui.name/knitr/

To ensure that the generated Markdown files follow the lesson template

guidelines, `source` the R file

[tools/chunk-options.R](tools/chunk-options.R). This file contains

settings that format the input and output code chunks, send all

generated figures to `fig/` instead of `figure/`, and specify a few

other knitr options. Thus a lesson should look like the following:

    ---

    layout: page

    title: Lesson Title

    subtitle: Topic Title

    minutes: 10

    ---

    ```{r, include=FALSE}

    source("tools/chunk-options.R")

    opts_chunk$set(fig.path = "fig/topic-title-")

    ```

    > ## Learning Objectives {.objectives}

    >

    > * Learning objective 1

    > * Learning objective 2

    Paragraphs of text

    --- possibly including [definitions](reference.html#definitions) ---

    mixed with:

    ```{r chunk-name}

    # code to be exectued

    ```

    More text.

When using [tools/chunk-options.R](tools/chunk-options.R), figures are

automatically sent to `fig/`. However it is easier to manage all the

figures in a lesson if their names are more descriptive. This can be

acheived by setting a more informative `fig.path` like the example

above, which will prepend "topic-title-" to all generated figure

names. Furthermore, it is recommended to name the code chunks. Thus if

a plot was generated in the example code chunk above, it would be

saved as `fig/topic-title-chunk-name.png`.

To avoid unecessary merge conflicts in the generated content, do not

randomly generate data. Instead use `set.seed` so that any randomly

generated data is always consistent. If introducing the concept of

random number generation is outside the scope of the lesson,

`set.seed` can be hidden from the learners in a separate code chunk.

    ```{r set-seed, echo=FALSE}

    set.seed(12345)

    ```

    ```{r normal-distribution}

    ex_dat <- rnorm(100)

    summary(ex_dat)

    ```

## Motivational Slides

Every lesson must include a short slide deck suitable for a short