---
############# DO NOT MODIFY ANY PART OF YAML EXCEPT THE AUTHOR ########################
title: "practice"
author: "type_your_name_here"
format: 
  html:
    embed-resources: true # ensures your figures/plots embed in the output file
---

## Tasks

1. Walk through quarto highlights with your instructor as they describe each component. 

2. Practice conducting a brief analysis with your instructor. Please follow along and type out your own code and interpretations. 

:::{.callout-important collapse=false}
## Pre-flight checklist
1. Make sure you set your view to be the source editor

2. Type in your name in the YML at the top where it currently says "type_your_name_here"

3. Save your quarto file in a folder that you will find it later, preferably in your OneDrive

4. Once your file is saved to a proper location, render the document to make sure it works
:::


In case you need it, here is the [Functions](https://pbreheny.org/4120/s26/labs/functions.html) document.


## Load libraries

```{r}
#| warning: false
#| message: false

library(ggplot2)
```

## Read in your data

We are going to use the `corn` dataset

Paste in the code from the course website and look at the first few lines of the data. 

```{r}
corn <- 0 # paste code here
  
head(corn)
```

## Goal

We are interested in whether the heights of corn are higher when they were produced by cross-fertilization instead of self-fertilization. Conduct a paired t-test in R to find if there is a significant difference in the effectiveness of these two methods.

### Visualize 

First, visualize the two distributions. 

```{r}
# construct two histograms here
ggplot()

# this is a density plot with the two distributions overlaid
# feel free to uncomment it out and take a look
# ggplot(corn) +
#   geom_density(aes(x=cross),fill= "snow3", alpha = .5) +
#   geom_density(aes(x=self), fill= "snow3", alpha = .5)

```


### Run t-test

```{r}

```

What do you conclude? 
