---
title: "Lecture 11"
author: "Matt Blackwell"
date: "2023-10-10"
output: pdf_document
---

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

## Covid data


```{r}
library(tidyverse)
library(gov50data)
covid_votes
```



```{r}
covid_votes |>
  mutate(
    one_dose_centered = one_dose_5plus_pct - mean(one_dose_5plus_pct, na.rm = TRUE),
    one_dose_z = one_dose_centered / sd(one_dose_5plus_pct, na.rm = TRUE)
  ) |>
  select(fips:state, one_dose_5plus_pct, one_dose_centered, one_dose_z)

```



```{r}
cor(covid_votes$one_dose_5plus_pct, covid_votes$dem_pct_2000,
    use = "pairwise")

```



```{r}
covid_votes |>
  ggplot(mapping = aes(x = dem_pct_2000, y = one_dose_5plus_pct)) + 
  geom_point(alpha = 0.25) +
  geom_smooth()
```


```{r}
z_score <- function(variable) {
  (variable - mean(variable, na.rm = TRUE)) / sd(variable, na.rm = TRUE)
}

z_score(variable = c(1,2,3,4,5))
```

```{r}
covid_votes |> 
  mutate(
    one_dose_5p_z = z_score(one_dose_5plus_pct),
    one_dose_65p_z = z_score(one_dose_65plus_pct)
  )
```