`rmarkdown`

**Lab Goal:** The goal of this lab is to introduce `rmarkdown`

!

You can use the .Rmd file that created this document as a template for this lab.

**[Exercise]** Write an unordered list of your classes this semester. Make the short course name (STAT 430) **bold**. Have the short course name link to the course description in the course explorer. Make the actual course title (Basics of Statistical Learning) *italic*.

**[Exercise]** Add a chunk to this document that sums the integers from `1`

to `100`

. It should display both the code and results after being knit. (Also, can you make this chunk only show output when knit? How about display the code, but don’t run the chunk when knit?)

The following code is “correct” but **terrible**. Don’t write code like this!

```
set.seed(1337);mu=10;sample_size=50;samples=100000;
x_bars=rep(0, samples)
for(i in 1:samples)
{
x_bars[i]=mean(rpois(sample_size,lambda = mu))}
x_bar_hist=hist(x_bars,breaks=50,main="Histogram of Sample Means",xlab="Sample Means",col="darkorange",border = "dodgerblue")
mean(x_bars>mu-2*sqrt(mu)/sqrt(sample_size)&x_bars<mu+2*sqrt(mu)/sqrt(sample_size))
```

**[Exercise]** Fix this code! You don’t need to change how the code accomplishes the task, but you should update the **style**. (Also, what is this code doing?)

`rnorm(10)`

```
set.seed(42)
rnorm(10)
```

**[Exercise]** Repeatedly run the (entire) two previous chunks. What’s the difference?

With RMarkdown, you can not only mix `R`

and `markdown`

, but you can also use LaTeX. It can be used inline: \(y = x + 2\) or in “equation mode,”

\[ a^2 + b^2 = c^2 \]

**[Exercise]** Write the density function for a normal distribution using LaTeX in equation mode.

- Hint: You can obtain the LaTeX for any equation in R4SL by right clicking it, selecting “Show Math As” then clicking “TeX Commands.”

Some other things to try:

- Can you make the plot above larger?
- Can you change the theme of this document?
- Can you add a table of contents to this document?

After this lab, we’ll do some more live coding to briefly discuss:

- Functions
- Vectors vs Lists
- Data Frames
- Tibbles
- Working interactively with
`rmarkdown`

- Importing data
- Why you should never, ever, set a
**working directory**

:)