---
title: "AE 3"
---

## 🕵️ Your turn: Michael Lacour 🕵️

Using the steps I just went through above, make up some data that pre-confirms some pattern about the world you wish were true:

1.  Change the [treatment]{.blue} and [outcome]{.red} variables in the code to ones of your choosing

2.  Alter the parameters in `rnorm()` so the values make sense for your variables (e.g., what is a reasonable distribution for age?)

3.  Make a scatterplot with a trend line -- use `labs()` to help us make sense of the plot axes!

```{r}

tibble()
```

## 🧩 Your turn: counterfactuals 🧩

With neighbor, think through the counterfactual scenarios in these examples. What is the implicit counterfactual? What would a good counterfactual look like?

1.  A study on whether international trade between two countries makes them more likely to form a defensive alliance.

2.  A study on whether being a victim of a crime makes someone more supportive of authoritarian leaders

3.  A study on whether those who served in the military are more likely to vote for "dovish" or "hawkish" candidates

4.  A study on whether post-*Dobbs* abortion restrictions reduced abortions