a)  **An R Markdown file is plain text file that contains what 3 important types of content?**

* An (optional) YAML header surrounded by ---s.
* Chunks of R code surrounded by three apostrophes
* Text mixed with simple text formatting like ```# heading``` and ```_italics_```.

b)  **What is a chunk and how do you add them? of the many chunk options which one do you think you will use the most and why? How is inline code different than code chunks?**

You add them in one of three ways
* The keyboard shortcut Cmd/Ctrl + Alt + I
* The “Insert” button icon in the editor toolbar.
* By manually typing the chunk delimiters

Based on the first two weeks, it seems like we will be using R chunks and Bash chunks a lot

Inline code can be used if you refer to your data/code in the text. Inline code is only in R but chunks can be in other languages and you can have difference settings applied to each chunk individually. 

c)  **What’s gone wrong with this code? Why are the points not blue?**

```
ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy, color = "blue"))
```

![plot](https://d33wubrfki0l68.cloudfront.net/fda836ccf904bda73f021f4802803bc134145ffa/0c9a7/visualize_files/figure-html/unnamed-chunk-11-1.png)

The color argument should not be applied to the aes() function, it should be outside the parathenses and applied to geom_point() function. 

Two ways of creating this plot from playing around with the arguments:

```
ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy, color = 1))

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy), color = "Blue")
```

Note, I do not have experience with ggplot. Just Base R plot functions from FISH 552/553

d)  **Of the many things we have done in class the past two weeks, what is one aspect you would like to revisit and spend more time on?**

I would like to revisit data organization. I think I've gotten comfortable with how github is organized but I'm still unsure of where my data should be. I realize data could be lots of places depending on the project and person, but some examples of good housekeeping (visually) would be helpful. If data is too big to go on github, where am I putting it?

The class just seems like a lot of new things all at once/ steep learning curve. But it now that we are starting our third week and things are more familiar, it's not as difficult. But still challenging.