---
title: "Data Wranglin'"
author: "Name"
output: pdf_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, message = FALSE, warning = FALSE,
                      fig.align = 'center', fig.width = 3, fig.height = 3)
```

```{r}
library(dplyr)

survey <- read.csv("https://collinn.github.io/data/wells_survey.csv")
```

# Problem Sets

**Question 1:** Sort students by division, and within division, by year.

```{r}

```


---


**Question 2:** For each division, determine the mean and standard deviation in the number of hours spent studying.

```{r}

```


---

**Question 3:** Calculate the median number of college applications submitted by students who play Wordle.

```{r}

```


---

**Question 4:** Determine the number of students who list each of the different locations as their preferred study place.

```{r}

```


---

**Question 5:** Identify students whose social views are more liberal than their economic views.

```{r}

```


---

**Question 6:** Create a data set consisting of two columns: height in centimeters and height in meters.

```{r}

```


---

**Question 7:** Count how many students think both that dogs should wear pants on their back legs and that hot dogs are sandwiches.

```{r}

```


---

**Question 8:** Create two new variables: one, a binary categorical indicating if their distance from home is less than 500 miles and a second binary categorical indicating if their primary mode of transportation is a car. Do these variables appear to be associated? What are some ways we could tell?

```{r}
library(ggplot2)

## Maybe include a plot with this one
```


---

**Question 9:** Create your own data wrangling question based on this survey data frame.

```{r}
## Create the question and solution!
```


---
