:::{.callout-note}
## Instruction

This is a quarto file. If you open its [source](report_template.qmd) in RStudio, you will get all the features of this interactive notebook-style document. If you want to know more about how to use this file to generate a .html document to hand in, look at [the getting started guide](https://quarto.org/docs/get-started/hello/rstudio.html).

(Delete this callout box before handing in your assignment.)
:::

```{r}
#| label: R packages
#| echo: false
#| warning: false
#| message: false

library(tidyverse)
# additional packages here
```

```{r}
#| label: data loading
#| echo: false

# your R code to load the data here
```

# Data description

Describe the data and use a visualization to support your story. (approx. one or two paragraphs)

```{r}
#| label: eda visualization

# your R code to generate the plot here

ggplot(mtcars, aes(x = wt, y = mpg)) +
  geom_point() +
  theme_minimal()
```

# Model description

Briefly describe which models you compare to perform prediction. (approx. two or three paragraphs)

# Data transformation and pre-processing

Describe additional pre-processing steps you have used, if any (e.g., dealing with categorical data, scaling). If you do not do any pre-processing, you can leave this section out.

# Model comparison

Describe how you compare the methods and why. (approx. two or three paragraphs)

# Chosen model

Show which method is best and why. (approx. one paragraph) You are welcome to use tables and plots!

```{r}
#| label: table example
data.frame(
  model       = c("Cool model 1", "Cool model 2"),
  performance = c(1.2, 1.8),
  other       = c(0.5, 0.3),
  notes       = c("Some note", "another note")
)
```

# Team member contributions

Write down what each team member contributed to the project.

- Author One: a, b, c
- Author Two: b, c, d
- Author Three: a, b, d
