---
title: "Term Project Proposal"
date: "Tuesday, March 21, 2023"
output:
  html_document:
    highlight: tango
    theme: cosmo
    toc: true
    toc_float: true
    toc_depth: 2
    collapsed: false
    smooth_scroll: false
    df_print: kable
---

```{r, include=FALSE}
knitr::opts_chunk$set(echo = FALSE, message = FALSE)
```

<!-- DO NOT EDIT ANYTHING ABOVE THIS LINE -->



# Team info

* Group name:
* Group members:



# Purpose

State your research question, a description of the variables you'll use, and
your data sources (please include [website links](https://www.uccs.edu/) if possible).

* Discuss the research question you will be addressing with your multiple regression model.


# Load packages and data

1. Load all necessary packages
1. Load the dataset then run the `clean_names()` function from the `janitor` package then `select()` only the variables you are going to use.

Example:

```{r, fig.width=16, fig.height=9, warning=TRUE}
library(ggplot2)
library(dplyr)
library(janitor)
library(fivethirtyeight)

bechdel <- bechdel %>% 
  clean_names() %>% 
  select(title, year, clean_test, domgross)

# Show only first 6 rows:
head(bechdel)
```



# Create EDA visualizations

Create "exploratory data analysis" visualizations of your data. At this point
these are preliminary and can change for the submission, but the only
requirement is that your visualizations use each of the *measurement variables*
included in your dataset to test out if they work.

```{r, fig.width=8, fig.height=4.5, warning=TRUE}
ggplot(data = bechdel, mapping = aes(x = domgross)) +
  geom_histogram() +
  labs(x = "Domestic earnings", title = "Earnings for Movies in Bechdel Dataset")
```

```{r, fig.width=8, fig.height=4.5, warning=TRUE}
ggplot(data = bechdel, mapping = aes(x = clean_test, y = domgross)) +
  geom_boxplot() +
  labs(x = "Bechdel test result", y = "Domestic earnings", title = "Earnings vs Bechdel Test Results")
```