```{r setup}
#| label: setup
#| message: false
#| echo: false

library(tidyverse)
theme_set(theme_light())
library(posterior)

library(brms)
library(broom.mixed)

options(ggplot2.discrete.fill = RColorBrewer::brewer.pal(8, "Dark2"))
options(ggplot2.discrete.colour = RColorBrewer::brewer.pal(8, "Dark2"))

options(dplyr.summarise.inform = FALSE)

my_seed <- 8878
```

## Introduction

This week's tutorial will be completely self guided.

To begin, download the `qml-stroop` repository from GitHub here: <https://github.com/uoelel/qml-stroop>:

- Click on the green button `Code`.
- Then `Download zip`.
- **Remember to unzip the downloaded zip archive**.
- Double click on `qml-stroop.Rproj` to open the RStudio project in RStudio.

::: callout-warning
#### Important

When working through this tutorial, always **make sure you are in the `qml-stroop` RStudio Project** you downloaded.

:::

## Modeling

- When modelling the data, you can pick **either reaction times or accuracy** as the outcome variables.
- As predictors include **condition** (congruent, incongruent, double incongruent).
- You can choose to also include **L1/L2 and/or languaguage proficiency** as predictors.
- Remember to include **interactions**.
- And of course feel free to fit models to both outcome variables!
