1. Snappy Title: Predictive Power and the Palmer Penguins

# 1. Snappy Title: Predictive Power and the Palmer Penguins
## 2. Descriptive title: Does bill length predict bill depth?
### 3. Authors: Dr. Reynolds

---

## 4. A compelling visual that has to do with your question:

![](https://allisonhorst.github.io/palmerpenguins/reference/figures/culmen_depth.png)

---

![](https://allisonhorst.github.io/palmerpenguins/reference/figures/lter_penguins.png)

---

``` r
install.packages("ggols")
```

And the development version from [GitHub](https://github.com/) with:

``` r
# install.packages("devtools")
devtools::install_github("EvaMaeRey/ggols")
```

---

## ggxmean gives us all the geom_lm_* functions

---

```r
*library(tidyverse)
```
]
 
.panel2-null-auto[

]

---
count: false

```r
library(tidyverse)
*library(ggxmean)
```
]
 
.panel2-null-auto[

]

---
count: false

```r
library(tidyverse)
library(ggxmean)

*ggplot(palmerpenguins::penguins)
```
]
 
.panel2-null-auto[
![](penguins_presentation_ggols_files/figure-html/null_auto_03_output-1.png)
]

---
count: false

```r
library(tidyverse)
library(ggxmean)

ggplot(palmerpenguins::penguins) +
* aes(x = bill_length_mm, y = bill_depth_mm)
```
]
 
.panel2-null-auto[
![](penguins_presentation_ggols_files/figure-html/null_auto_04_output-1.png)
]

---
count: false

```r
library(tidyverse)
library(ggxmean)

ggplot(palmerpenguins::penguins) +
  aes(x = bill_length_mm, y = bill_depth_mm) +
* geom_point()
```
]
 
.panel2-null-auto[
![](penguins_presentation_ggols_files/figure-html/null_auto_05_output-1.png)
]

---
count: false

```r
library(tidyverse)
library(ggxmean)

ggplot(palmerpenguins::penguins) +
  aes(x = bill_length_mm, y = bill_depth_mm) +
  geom_point() +
* geom_y_mean()
```
]
 
.panel2-null-auto[
![](penguins_presentation_ggols_files/figure-html/null_auto_06_output-1.png)
]

---
count: false

```r
library(tidyverse)
library(ggxmean)

ggplot(palmerpenguins::penguins) +
  aes(x = bill_length_mm, y = bill_depth_mm) +
  geom_point() +
  geom_y_mean() +
* ggxmean:::geom_ydiff(color = "darkred")
```
]
 
.panel2-null-auto[
![](penguins_presentation_ggols_files/figure-html/null_auto_07_output-1.png)
]

---
count: false

```r
library(tidyverse)
library(ggxmean)

ggplot(palmerpenguins::penguins) +
  aes(x = bill_length_mm, y = bill_depth_mm) +
  geom_point() +
  geom_y_mean() +
  ggxmean:::geom_ydiff(color = "darkred") +
* geom_y_mean_label()
```
]
 
.panel2-null-auto[
![](penguins_presentation_ggols_files/figure-html/null_auto_08_output-1.png)
]

---

```r
*library(tidyverse)
```
]
 
.panel2-x-auto[

]

---
count: false

```r
library(tidyverse)
*library(ggxmean)
```
]
 
.panel2-x-auto[

]

---
count: false

```r
library(tidyverse)
library(ggxmean)

*ggplot(palmerpenguins::penguins)
```
]
 
.panel2-x-auto[
![](penguins_presentation_ggols_files/figure-html/x_auto_03_output-1.png)
]

---
count: false

```r
library(tidyverse)
library(ggxmean)

ggplot(palmerpenguins::penguins) +
* aes(y = bill_depth_mm,
*     x = bill_length_mm)
```
]
 
.panel2-x-auto[
![](penguins_presentation_ggols_files/figure-html/x_auto_04_output-1.png)
]

---
count: false

```r
library(tidyverse)
library(ggxmean)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm,
      x = bill_length_mm) +
* geom_point()
```
]
 
.panel2-x-auto[
![](penguins_presentation_ggols_files/figure-html/x_auto_05_output-1.png)
]

---
count: false

```r
library(tidyverse)
library(ggxmean)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm,
      x = bill_length_mm) +
  geom_point() +
* geom_lm()
```
]
 
.panel2-x-auto[
![](penguins_presentation_ggols_files/figure-html/x_auto_06_output-1.png)
]

---
count: false

```r
library(tidyverse)
library(ggxmean)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm,
      x = bill_length_mm) +
  geom_point() +
  geom_lm() +
* geom_lm_conf_int()
```
]
 
.panel2-x-auto[
![](penguins_presentation_ggols_files/figure-html/x_auto_07_output-1.png)
]

---
count: false

```r
library(tidyverse)
library(ggxmean)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm,
      x = bill_length_mm) +
  geom_point() +
  geom_lm() +
  geom_lm_conf_int() +
* geom_lm_residuals(color = "darkred")
```
]
 
.panel2-x-auto[
![](penguins_presentation_ggols_files/figure-html/x_auto_08_output-1.png)
]

---
count: false

```r
library(tidyverse)
library(ggxmean)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm,
      x = bill_length_mm) +
  geom_point() +
  geom_lm() +
  geom_lm_conf_int() +
  geom_lm_residuals(color = "darkred") +
* geom_lm_fitted()
```
]
 
.panel2-x-auto[
![](penguins_presentation_ggols_files/figure-html/x_auto_09_output-1.png)
]

---
count: false

```r
library(tidyverse)
library(ggxmean)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm,
      x = bill_length_mm) +
  geom_point() +
  geom_lm() +
  geom_lm_conf_int() +
  geom_lm_residuals(color = "darkred") +
  geom_lm_fitted() +
* geom_lm_formula()
```
]
 
.panel2-x-auto[
![](penguins_presentation_ggols_files/figure-html/x_auto_10_output-1.png)
]

---
count: false

```r
library(tidyverse)
library(ggxmean)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm,
      x = bill_length_mm) +
  geom_point() +
  geom_lm() +
  geom_lm_conf_int() +
  geom_lm_residuals(color = "darkred") +
  geom_lm_fitted() +
  geom_lm_formula() +
* ggols:::geom_lm_rsquared()   #should be moved to ggxmean
```
]
 
.panel2-x-auto[
![](penguins_presentation_ggols_files/figure-html/x_auto_11_output-1.png)
]

---
count: false

```r
library(tidyverse)
library(ggxmean)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm,
      x = bill_length_mm) +
  geom_point() +
  geom_lm() +
  geom_lm_conf_int() +
  geom_lm_residuals(color = "darkred") +
  geom_lm_fitted() +
  geom_lm_formula() +
  ggols:::geom_lm_rsquared() +  #should be moved to ggxmean
* geom_lm_intercept_label(hjust = -.2)
```
]
 
.panel2-x-auto[
![](penguins_presentation_ggols_files/figure-html/x_auto_12_output-1.png)
]

---
count: false

```r
library(tidyverse)
library(ggxmean)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm,
      x = bill_length_mm) +
  geom_point() +
  geom_lm() +
  geom_lm_conf_int() +
  geom_lm_residuals(color = "darkred") +
  geom_lm_fitted() +
  geom_lm_formula() +
  ggols:::geom_lm_rsquared() +  #should be moved to ggxmean
  geom_lm_intercept_label(hjust = -.2) +
* geom_lm_intercept(color = "blue")
```
]
 
.panel2-x-auto[
![](penguins_presentation_ggols_files/figure-html/x_auto_13_output-1.png)
]

---
class: inverse, center, middle

# Visualization, adding indicator var

---

```r
*library(ggols)
```
]
 
.panel2-indicator-auto[

]

---
count: false

```r
library(ggols)

*ggplot(palmerpenguins::penguins)
```
]
 
.panel2-indicator-auto[
![](penguins_presentation_ggols_files/figure-html/indicator_auto_02_output-1.png)
]

---
count: false

```r
library(ggols)

ggplot(palmerpenguins::penguins) +
* aes(y = bill_depth_mm, x = bill_length_mm)
```
]
 
.panel2-indicator-auto[
![](penguins_presentation_ggols_files/figure-html/indicator_auto_03_output-1.png)
]

---
count: false

```r
library(ggols)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
* geom_point()
```
]
 
.panel2-indicator-auto[
![](penguins_presentation_ggols_files/figure-html/indicator_auto_04_output-1.png)
]

---
count: false

```r
library(ggols)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
* aes(color = species)
```
]
 
.panel2-indicator-auto[
![](penguins_presentation_ggols_files/figure-html/indicator_auto_05_output-1.png)
]

---
count: false

```r
library(ggols)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
  aes(color = species) +
* aes(indicator = species)
```
]
 
.panel2-indicator-auto[
![](penguins_presentation_ggols_files/figure-html/indicator_auto_06_output-1.png)
]

---
count: false

```r
library(ggols)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
  aes(color = species) +
  aes(indicator = species) +
* geom_lm_indicator()
```
]
 
.panel2-indicator-auto[
![](penguins_presentation_ggols_files/figure-html/indicator_auto_07_output-1.png)
]

---
count: false

```r
library(ggols)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
  aes(color = species) +
  aes(indicator = species) +
  geom_lm_indicator() +
* geom_lm_indicator_conf_int()
```
]
 
.panel2-indicator-auto[
![](penguins_presentation_ggols_files/figure-html/indicator_auto_08_output-1.png)
]

---
count: false

```r
library(ggols)

---
count: false

```r
library(ggols)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
  aes(color = species) +
  aes(indicator = species) +
  geom_lm_indicator() +
  geom_lm_indicator_conf_int() +
  geom_lm_indicator_residuals(color = "darkred") +
* geom_lm_indicator_fitted()
```
]
 
.panel2-indicator-auto[
![](penguins_presentation_ggols_files/figure-html/indicator_auto_10_output-1.png)
]

---
count: false

```r
library(ggols)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
  aes(color = species) +
  aes(indicator = species) +
  geom_lm_indicator() +
  geom_lm_indicator_conf_int() +
  geom_lm_indicator_residuals(color = "darkred") +
  geom_lm_indicator_fitted() +
* geom_lm_indicator_formula()
```
]
 
.panel2-indicator-auto[
![](penguins_presentation_ggols_files/figure-html/indicator_auto_11_output-1.png)
]

---
count: false

```r
library(ggols)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
  aes(color = species) +
  aes(indicator = species) +
  geom_lm_indicator() +
  geom_lm_indicator_conf_int() +
  geom_lm_indicator_residuals(color = "darkred") +
  geom_lm_indicator_fitted() +
  geom_lm_indicator_formula() +
* geom_lm_indicator_rsquared()
```
]
 
.panel2-indicator-auto[
![](penguins_presentation_ggols_files/figure-html/indicator_auto_12_output-1.png)
]

---
count: false

```r
library(ggols)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
  aes(color = species) +
  aes(indicator = species) +
  geom_lm_indicator() +
  geom_lm_indicator_conf_int() +
  geom_lm_indicator_residuals(color = "darkred") +
  geom_lm_indicator_fitted() +
  geom_lm_indicator_formula() +
  geom_lm_indicator_rsquared() +
* geom_lm_indicator_intercept(color = "blue")
```
]
 
.panel2-indicator-auto[
![](penguins_presentation_ggols_files/figure-html/indicator_auto_13_output-1.png)
]

---
count: false

```r
library(ggols)

ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
  aes(color = species) +
  aes(indicator = species) +
  geom_lm_indicator() +
  geom_lm_indicator_conf_int() +
  geom_lm_indicator_residuals(color = "darkred") +
  geom_lm_indicator_fitted() +
  geom_lm_indicator_formula() +
  geom_lm_indicator_rsquared() +
  geom_lm_indicator_intercept(color = "blue") +
* geom_lm_indicator_intercept_label(hjust = -.2)
```
]
 
.panel2-indicator-auto[
![](penguins_presentation_ggols_files/figure-html/indicator_auto_14_output-1.png)
]

---
class: inverse, center, middle

# Visualization, adding indicator interaction

---

```r
*ggplot(palmerpenguins::penguins)
```
]
 
.panel2-interaction-auto[
![](penguins_presentation_ggols_files/figure-html/interaction_auto_01_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
* aes(y = bill_depth_mm, x = bill_length_mm)
```
]
 
.panel2-interaction-auto[
![](penguins_presentation_ggols_files/figure-html/interaction_auto_02_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
* geom_point()
```
]
 
.panel2-interaction-auto[
![](penguins_presentation_ggols_files/figure-html/interaction_auto_03_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
* aes(color = species)
```
]
 
.panel2-interaction-auto[
![](penguins_presentation_ggols_files/figure-html/interaction_auto_04_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
  aes(color = species) +
* aes(indicator = species)
```
]
 
.panel2-interaction-auto[
![](penguins_presentation_ggols_files/figure-html/interaction_auto_05_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
  aes(color = species) +
  aes(indicator = species) +
* geom_lm_interaction()
```
]
 
.panel2-interaction-auto[
![](penguins_presentation_ggols_files/figure-html/interaction_auto_06_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
  aes(color = species) +
  aes(indicator = species) +
  geom_lm_interaction() +
* geom_lm_interaction_conf_int()
```
]
 
.panel2-interaction-auto[
![](penguins_presentation_ggols_files/figure-html/interaction_auto_07_output-1.png)
]

---
count: false

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
  aes(color = species) +
  aes(indicator = species) +
  geom_lm_interaction() +
  geom_lm_interaction_conf_int() +
  geom_lm_interaction_residuals(color = "darkred") +
* geom_lm_interaction_fitted()
```
]
 
.panel2-interaction-auto[
![](penguins_presentation_ggols_files/figure-html/interaction_auto_09_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
  aes(color = species) +
  aes(indicator = species) +
  geom_lm_interaction() +
  geom_lm_interaction_conf_int() +
  geom_lm_interaction_residuals(color = "darkred") +
  geom_lm_interaction_fitted() +
* geom_lm_interaction_formula()
```
]
 
.panel2-interaction-auto[
![](penguins_presentation_ggols_files/figure-html/interaction_auto_10_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
  aes(color = species) +
  aes(indicator = species) +
  geom_lm_interaction() +
  geom_lm_interaction_conf_int() +
  geom_lm_interaction_residuals(color = "darkred") +
  geom_lm_interaction_fitted() +
  geom_lm_interaction_formula() +
* geom_lm_interaction_rsquared()
```
]
 
.panel2-interaction-auto[
![](penguins_presentation_ggols_files/figure-html/interaction_auto_11_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
  aes(color = species) +
  aes(indicator = species) +
  geom_lm_interaction() +
  geom_lm_interaction_conf_int() +
  geom_lm_interaction_residuals(color = "darkred") +
  geom_lm_interaction_fitted() +
  geom_lm_interaction_formula() +
  geom_lm_interaction_rsquared() +
* geom_lm_interaction_intercept(color = "blue")
```
]
 
.panel2-interaction-auto[
![](penguins_presentation_ggols_files/figure-html/interaction_auto_12_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(y = bill_depth_mm, x = bill_length_mm) +
  geom_point() +
  aes(color = species) +
  aes(indicator = species) +
  geom_lm_interaction() +
  geom_lm_interaction_conf_int() +
  geom_lm_interaction_residuals(color = "darkred") +
  geom_lm_interaction_fitted() +
  geom_lm_interaction_formula() +
  geom_lm_interaction_rsquared() +
  geom_lm_interaction_intercept(color = "blue") +
* geom_lm_interaction_intercept_label(hjust = -.2)
```
]
 
.panel2-interaction-auto[
![](penguins_presentation_ggols_files/figure-html/interaction_auto_13_output-1.png)
]

---
class: inverse, center, middle

# Visualization, and two indicator variables

---

```r
*ggplot(palmerpenguins::penguins)
```
]
 
.panel2-int2-auto[
![](penguins_presentation_ggols_files/figure-html/int2_auto_01_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
* aes(x = bill_length_mm, y = bill_depth_mm,
*     indicator = species, indicator2 = sex,
*     color = species, shape = sex)
```
]
 
.panel2-int2-auto[
![](penguins_presentation_ggols_files/figure-html/int2_auto_02_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(x = bill_length_mm, y = bill_depth_mm,
      indicator = species, indicator2 = sex,
      color = species, shape = sex) +
* geom_point()
```
]
 
.panel2-int2-auto[
![](penguins_presentation_ggols_files/figure-html/int2_auto_03_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(x = bill_length_mm, y = bill_depth_mm,
      indicator = species, indicator2 = sex,
      color = species, shape = sex) +
  geom_point() +
* geom_lm_indicator2()
```
]
 
.panel2-int2-auto[
![](penguins_presentation_ggols_files/figure-html/int2_auto_04_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(x = bill_length_mm, y = bill_depth_mm,
      indicator = species, indicator2 = sex,
      color = species, shape = sex) +
  geom_point() +
  geom_lm_indicator2() +
* geom_lm_indicator2_conf_int()
```
]
 
.panel2-int2-auto[
![](penguins_presentation_ggols_files/figure-html/int2_auto_05_output-1.png)
]

---
count: false

---
count: false

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(x = bill_length_mm, y = bill_depth_mm,
      indicator = species, indicator2 = sex,
      color = species, shape = sex) +
  geom_point() +
  geom_lm_indicator2() +
  geom_lm_indicator2_conf_int() +
  geom_lm_indicator2_residuals(color = "darkred") +
  geom_lm_indicator2_fitted() +
* geom_lm_indicator2_formula()
```
]
 
.panel2-int2-auto[
![](penguins_presentation_ggols_files/figure-html/int2_auto_08_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(x = bill_length_mm, y = bill_depth_mm,
      indicator = species, indicator2 = sex,
      color = species, shape = sex) +
  geom_point() +
  geom_lm_indicator2() +
  geom_lm_indicator2_conf_int() +
  geom_lm_indicator2_residuals(color = "darkred") +
  geom_lm_indicator2_fitted() +
  geom_lm_indicator2_formula() +
* geom_lm_indicator2_rsquared()
```
]
 
.panel2-int2-auto[
![](penguins_presentation_ggols_files/figure-html/int2_auto_09_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(x = bill_length_mm, y = bill_depth_mm,
      indicator = species, indicator2 = sex,
      color = species, shape = sex) +
  geom_point() +
  geom_lm_indicator2() +
  geom_lm_indicator2_conf_int() +
  geom_lm_indicator2_residuals(color = "darkred") +
  geom_lm_indicator2_fitted() +
  geom_lm_indicator2_formula() +
  geom_lm_indicator2_rsquared() +
* geom_lm_indicator2_intercept(color = "blue")
```
]
 
.panel2-int2-auto[
![](penguins_presentation_ggols_files/figure-html/int2_auto_10_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(x = bill_length_mm, y = bill_depth_mm,
      indicator = species, indicator2 = sex,
      color = species, shape = sex) +
  geom_point() +
  geom_lm_indicator2() +
  geom_lm_indicator2_conf_int() +
  geom_lm_indicator2_residuals(color = "darkred") +
  geom_lm_indicator2_fitted() +
  geom_lm_indicator2_formula() +
  geom_lm_indicator2_rsquared() +
  geom_lm_indicator2_intercept(color = "blue") +
* geom_lm_indicator2_intercept_label(hjust = -.2)
```
]
 
.panel2-int2-auto[
![](penguins_presentation_ggols_files/figure-html/int2_auto_11_output-1.png)
]

---
count: false

```r
ggplot(palmerpenguins::penguins) +
  aes(x = bill_length_mm, y = bill_depth_mm,
      indicator = species, indicator2 = sex,
      color = species, shape = sex) +
  geom_point() +
  geom_lm_indicator2() +
  geom_lm_indicator2_conf_int() +
  geom_lm_indicator2_residuals(color = "darkred") +
  geom_lm_indicator2_fitted() +
  geom_lm_indicator2_formula() +
  geom_lm_indicator2_rsquared() +
  geom_lm_indicator2_intercept(color = "blue") +
  geom_lm_indicator2_intercept_label(hjust = -.2) +
* labs(title = "Penguins!")
```
]
 
.panel2-int2-auto[
![](penguins_presentation_ggols_files/figure-html/int2_auto_12_output-1.png)
]

---
class: inverse, center, middle

# big picture walk through

---

![](penguins_presentation_ggols_files/figure-html/null2-1.png)

---

![](penguins_presentation_ggols_files/figure-html/x2-1.png)

---

![](penguins_presentation_ggols_files/figure-html/indicator2-1.png)

---

![](penguins_presentation_ggols_files/figure-html/interaction2-1.png)

---

![](penguins_presentation_ggols_files/figure-html/int22-1.png)

---
class: inverse, center, middle

# beyond penguins:  are we portable?

---

```r
spotify_songs <- read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-01-21/spotify_songs.csv')
```

---

```r
*spotify_songs
```
]
 
.panel2-spot-auto[

```
# A tibble: 32,833 × 23
   track_id              track_name track_artist track_popularity track_album_id
   <chr>                 <chr>      <chr>                   <dbl> <chr>         
 1 6f807x0ima9a1j3VPbc7… I Don't C… Ed Sheeran                 66 2oCs0DGTsRO98…
 2 0r7CVbZTWZgbTCYdfa2P… Memories … Maroon 5                   67 63rPSO264uRjW…
 3 1z1Hg7Vb0AhHDiEmnDE7… All the T… Zara Larsson               70 1HoSmj2eLcsrR…
 4 75FpbthrwQmzHlBJLuGd… Call You … The Chainsm…               60 1nqYsOef1yKKu…
 5 1e8PAfcKUYoKkxPhrHqw… Someone Y… Lewis Capal…               69 7m7vv9wlQ4i0L…
 6 7fvUMiyapMsRRxr07cU8… Beautiful… Ed Sheeran                 67 2yiy9cd2QktrN…
 7 2OAylPUDDfwRGfe0lYql… Never Rea… Katy Perry                 62 7INHYSeusaFly…
 8 6b1RNvAcJjQH73eZO4BL… Post Malo… Sam Feldt                  69 6703SRPsLkS4b…
 9 7bF6tCO3gFb8INrEDcjN… Tough Lov… Avicii                     68 7CvAfGvq4RlIw…
10 1IXGILkPm0tOCNeq00kC… If I Can'… Shawn Mendes               67 4QxzbfSsVryEQ…
# … with 32,823 more rows, and 18 more variables: track_album_name <chr>,
#   track_album_release_date <chr>, playlist_name <chr>, playlist_id <chr>,
#   playlist_genre <chr>, playlist_subgenre <chr>, danceability <dbl>,
#   energy <dbl>, key <dbl>, loudness <dbl>, mode <dbl>, speechiness <dbl>,
#   acousticness <dbl>, instrumentalness <dbl>, liveness <dbl>, valence <dbl>,
#   tempo <dbl>, duration_ms <dbl>
```
]

---
count: false

```r
spotify_songs %>%
* filter(track_popularity > 0)
```
]
 
.panel2-spot-auto[

```
# A tibble: 30,130 × 23
   track_id              track_name track_artist track_popularity track_album_id
   <chr>                 <chr>      <chr>                   <dbl> <chr>         
 1 6f807x0ima9a1j3VPbc7… I Don't C… Ed Sheeran                 66 2oCs0DGTsRO98…
 2 0r7CVbZTWZgbTCYdfa2P… Memories … Maroon 5                   67 63rPSO264uRjW…
 3 1z1Hg7Vb0AhHDiEmnDE7… All the T… Zara Larsson               70 1HoSmj2eLcsrR…
 4 75FpbthrwQmzHlBJLuGd… Call You … The Chainsm…               60 1nqYsOef1yKKu…
 5 1e8PAfcKUYoKkxPhrHqw… Someone Y… Lewis Capal…               69 7m7vv9wlQ4i0L…
 6 7fvUMiyapMsRRxr07cU8… Beautiful… Ed Sheeran                 67 2yiy9cd2QktrN…
 7 2OAylPUDDfwRGfe0lYql… Never Rea… Katy Perry                 62 7INHYSeusaFly…
 8 6b1RNvAcJjQH73eZO4BL… Post Malo… Sam Feldt                  69 6703SRPsLkS4b…
 9 7bF6tCO3gFb8INrEDcjN… Tough Lov… Avicii                     68 7CvAfGvq4RlIw…
10 1IXGILkPm0tOCNeq00kC… If I Can'… Shawn Mendes               67 4QxzbfSsVryEQ…
# … with 30,120 more rows, and 18 more variables: track_album_name <chr>,
#   track_album_release_date <chr>, playlist_name <chr>, playlist_id <chr>,
#   playlist_genre <chr>, playlist_subgenre <chr>, danceability <dbl>,
#   energy <dbl>, key <dbl>, loudness <dbl>, mode <dbl>, speechiness <dbl>,
#   acousticness <dbl>, instrumentalness <dbl>, liveness <dbl>, valence <dbl>,
#   tempo <dbl>, duration_ms <dbl>
```
]

---
count: false

```r
spotify_songs %>%
  filter(track_popularity > 0) %>%
* mutate(latin = case_when(playlist_genre == "latin" ~ "Latin",
*                              TRUE ~"not Latin"))
```
]
 
.panel2-spot-auto[

```
# A tibble: 30,130 × 24
   track_id              track_name track_artist track_popularity track_album_id
   <chr>                 <chr>      <chr>                   <dbl> <chr>         
 1 6f807x0ima9a1j3VPbc7… I Don't C… Ed Sheeran                 66 2oCs0DGTsRO98…
 2 0r7CVbZTWZgbTCYdfa2P… Memories … Maroon 5                   67 63rPSO264uRjW…
 3 1z1Hg7Vb0AhHDiEmnDE7… All the T… Zara Larsson               70 1HoSmj2eLcsrR…
 4 75FpbthrwQmzHlBJLuGd… Call You … The Chainsm…               60 1nqYsOef1yKKu…
 5 1e8PAfcKUYoKkxPhrHqw… Someone Y… Lewis Capal…               69 7m7vv9wlQ4i0L…
 6 7fvUMiyapMsRRxr07cU8… Beautiful… Ed Sheeran                 67 2yiy9cd2QktrN…
 7 2OAylPUDDfwRGfe0lYql… Never Rea… Katy Perry                 62 7INHYSeusaFly…
 8 6b1RNvAcJjQH73eZO4BL… Post Malo… Sam Feldt                  69 6703SRPsLkS4b…
 9 7bF6tCO3gFb8INrEDcjN… Tough Lov… Avicii                     68 7CvAfGvq4RlIw…
10 1IXGILkPm0tOCNeq00kC… If I Can'… Shawn Mendes               67 4QxzbfSsVryEQ…
# … with 30,120 more rows, and 19 more variables: track_album_name <chr>,
#   track_album_release_date <chr>, playlist_name <chr>, playlist_id <chr>,
#   playlist_genre <chr>, playlist_subgenre <chr>, danceability <dbl>,
#   energy <dbl>, key <dbl>, loudness <dbl>, mode <dbl>, speechiness <dbl>,
#   acousticness <dbl>, instrumentalness <dbl>, liveness <dbl>, valence <dbl>,
#   tempo <dbl>, duration_ms <dbl>, latin <chr>
```
]

---
count: false

```r
spotify_songs %>%
  filter(track_popularity > 0) %>%
  mutate(latin = case_when(playlist_genre == "latin" ~ "Latin",
                               TRUE ~"not Latin")) %>%
* mutate(latin = fct_rev(latin))
```
]
 
.panel2-spot-auto[

---
count: false

```r
spotify_songs %>%
  filter(track_popularity > 0) %>%
  mutate(latin = case_when(playlist_genre == "latin" ~ "Latin",
                               TRUE ~"not Latin")) %>%
  mutate(latin = fct_rev(latin)) ->
*prep
```
]
 
.panel2-spot-auto[

]

---
count: false

*set.seed(12345)
```
]
 
.panel2-spot-auto[

]

---
count: false

set.seed(12345)
*prep
```
]
 
.panel2-spot-auto[

---
count: false

set.seed(12345)
prep %>%
* ggplot()
```
]
 
.panel2-spot-auto[
![](penguins_presentation_ggols_files/figure-html/spot_auto_08_output-1.png)
]

---
count: false

set.seed(12345)
prep %>%
  ggplot() +
* aes(y = track_popularity,
*     x = danceability,
*     indicator = latin,
*     color = latin)
```
]
 
.panel2-spot-auto[
![](penguins_presentation_ggols_files/figure-html/spot_auto_09_output-1.png)
]

---
count: false

set.seed(12345)
prep %>%
  ggplot() +
  aes(y = track_popularity,
      x = danceability,
      indicator = latin,
      color = latin) +
* geom_point(alpha = .05)
```
]
 
.panel2-spot-auto[
![](penguins_presentation_ggols_files/figure-html/spot_auto_10_output-1.png)
]

---
count: false

set.seed(12345)
prep %>%
  ggplot() +
  aes(y = track_popularity,
      x = danceability,
      indicator = latin,
      color = latin) +
  geom_point(alpha = .05) +
* geom_point(data = . %>% slice_sample(prop = .02),
*            shape = 21, fill = "white")
```
]
 
.panel2-spot-auto[
![](penguins_presentation_ggols_files/figure-html/spot_auto_11_output-1.png)
]

---
count: false

set.seed(12345)
prep %>%
  ggplot() +
  aes(y = track_popularity,
      x = danceability,
      indicator = latin,
      color = latin) +
  geom_point(alpha = .05) +
  geom_point(data = . %>% slice_sample(prop = .02),
             shape = 21, fill = "white") +
* geom_lm_indicator()
```
]
 
.panel2-spot-auto[
![](penguins_presentation_ggols_files/figure-html/spot_auto_12_output-1.png)
]

---
count: false

set.seed(12345)
prep %>%
  ggplot() +
  aes(y = track_popularity,
      x = danceability,
      indicator = latin,
      color = latin) +
  geom_point(alpha = .05) +
  geom_point(data = . %>% slice_sample(prop = .02),
             shape = 21, fill = "white") +
  geom_lm_indicator() +
* geom_lm_indicator_conf_int()
```
]
 
.panel2-spot-auto[
![](penguins_presentation_ggols_files/figure-html/spot_auto_13_output-1.png)
]

---
count: false

set.seed(12345)
prep %>%
  ggplot() +
  aes(y = track_popularity,
      x = danceability,
      indicator = latin,
      color = latin) +
  geom_point(alpha = .05) +
  geom_point(data = . %>% slice_sample(prop = .02),
             shape = 21, fill = "white") +
  geom_lm_indicator() +
  geom_lm_indicator_conf_int() +
* geom_lm_indicator_formula()
```
]
 
.panel2-spot-auto[
![](penguins_presentation_ggols_files/figure-html/spot_auto_14_output-1.png)
]

---
count: false

set.seed(12345)
prep %>%
  ggplot() +
  aes(y = track_popularity,
      x = danceability,
      indicator = latin,
      color = latin) +
  geom_point(alpha = .05) +
  geom_point(data = . %>% slice_sample(prop = .02),
             shape = 21, fill = "white") +
  geom_lm_indicator() +
  geom_lm_indicator_conf_int() +
  geom_lm_indicator_formula() +
* labs(title = "Songs!",
*      subtitle = "Among songs w/ >0 in track popularity")
```
]
 
.panel2-spot-auto[
![](penguins_presentation_ggols_files/figure-html/spot_auto_15_output-1.png)
]

---
count: false

set.seed(12345)
prep %>%
  ggplot() +
  aes(y = track_popularity,
      x = danceability,
      indicator = latin,
      color = latin) +
  geom_point(alpha = .05) +
  geom_point(data = . %>% slice_sample(prop = .02),
             shape = 21, fill = "white") +
  geom_lm_indicator() +
  geom_lm_indicator_conf_int() +
  geom_lm_indicator_formula() +
  labs(title = "Songs!",
       subtitle = "Among songs w/ >0 in track popularity") +
* labs(color = NULL)
```
]
 
.panel2-spot-auto[
![](penguins_presentation_ggols_files/figure-html/spot_auto_16_output-1.png)
]

---
count: false

set.seed(12345)
prep %>%
  ggplot() +
  aes(y = track_popularity,
      x = danceability,
      indicator = latin,
      color = latin) +
  geom_point(alpha = .05) +
  geom_point(data = . %>% slice_sample(prop = .02),
             shape = 21, fill = "white") +
  geom_lm_indicator() +
  geom_lm_indicator_conf_int() +
  geom_lm_indicator_formula() +
  labs(title = "Songs!",
       subtitle = "Among songs w/ >0 in track popularity") +
  labs(color = NULL) +
* geom_lm_indicator_intercept()
```
]
 
.panel2-spot-auto[
![](penguins_presentation_ggols_files/figure-html/spot_auto_17_output-1.png)
]

---

```r
*ma206data::chap10_CatJumpingFull
```
]
 
.panel2-cats-auto[

```
# A tibble: 18 × 7
   cat_id body_mass_g hind_limb_length_cm muscle_mass_g percent_body_fat
    <dbl>       <dbl>               <dbl>         <dbl>            <dbl>
 1      1        3640                29.1          51.2               29
 2      2        2670                28.6          46.0               17
 3      3        5600                31.7          95.9               31
 4      4        4130                26.9          55.6               39
 5      5        3020                26.1          57.2               15
 6      6        2660                26.7          48.7               11
 7      7        3240                26.7          64.6               21
 8      8        5140                27.7          78.8               35
 9      9        3690                25.5          54.6               33
10     10        3620                28.2          55.5               15
11     11        5310                28.4          68.8               42
12     12        5560                28.6          79.8               37
13     13        3970                29.8          69.4               20
14     14        3770                26.7          60.2               26
15     15        5100                27.8          60.7               41
16     16        2950                27.9          55.6               25
17     17        7930                30.6          99.0               48
18     18        3550                28.1          79.2               16
# … with 2 more variables: takeoff_velocity_cm_sec <dbl>, sex_0_f_1_m <dbl>
```
]

---
count: false

```r
ma206data::chap10_CatJumpingFull %>%
* mutate(sex = case_when(sex_0_f_1_m == 0 ~ "Female",
*                        sex_0_f_1_m == 1 ~ "Male"))
```
]
 
.panel2-cats-auto[

```
# A tibble: 18 × 8
   cat_id body_mass_g hind_limb_length_cm muscle_mass_g percent_body_fat
    <dbl>       <dbl>               <dbl>         <dbl>            <dbl>
 1      1        3640                29.1          51.2               29
 2      2        2670                28.6          46.0               17
 3      3        5600                31.7          95.9               31
 4      4        4130                26.9          55.6               39
 5      5        3020                26.1          57.2               15
 6      6        2660                26.7          48.7               11
 7      7        3240                26.7          64.6               21
 8      8        5140                27.7          78.8               35
 9      9        3690                25.5          54.6               33
10     10        3620                28.2          55.5               15
11     11        5310                28.4          68.8               42
12     12        5560                28.6          79.8               37
13     13        3970                29.8          69.4               20
14     14        3770                26.7          60.2               26
15     15        5100                27.8          60.7               41
16     16        2950                27.9          55.6               25
17     17        7930                30.6          99.0               48
18     18        3550                28.1          79.2               16
# … with 3 more variables: takeoff_velocity_cm_sec <dbl>, sex_0_f_1_m <dbl>,
#   sex <chr>
```
]

---
count: false

```r
ma206data::chap10_CatJumpingFull %>%
  mutate(sex = case_when(sex_0_f_1_m == 0 ~ "Female",
                         sex_0_f_1_m == 1 ~ "Male")) %>%
* mutate(sex = factor(sex))
```
]
 
.panel2-cats-auto[

---
count: false

```r
ma206data::chap10_CatJumpingFull %>%
  mutate(sex = case_when(sex_0_f_1_m == 0 ~ "Female",
                         sex_0_f_1_m == 1 ~ "Male")) %>%
  mutate(sex = factor(sex)) %>%
* ggplot()
```
]
 
.panel2-cats-auto[
![](penguins_presentation_ggols_files/figure-html/cats_auto_04_output-1.png)
]

---
count: false

```r
ma206data::chap10_CatJumpingFull %>%
  mutate(sex = case_when(sex_0_f_1_m == 0 ~ "Female",
                         sex_0_f_1_m == 1 ~ "Male")) %>%
  mutate(sex = factor(sex)) %>%
  ggplot() +
* aes(y = muscle_mass_g,
*     x = body_mass_g)
```
]
 
.panel2-cats-auto[
![](penguins_presentation_ggols_files/figure-html/cats_auto_05_output-1.png)
]

---
count: false

---
count: false

---
count: false

---
count: false

```r
ma206data::chap10_CatJumpingFull %>%
  mutate(sex = case_when(sex_0_f_1_m == 0 ~ "Female",
                         sex_0_f_1_m == 1 ~ "Male")) %>%
  mutate(sex = factor(sex)) %>%
  ggplot() +
  aes(y = muscle_mass_g,
      x = body_mass_g) +
  geom_point(shape = 21, fill = "white", size = 1,
             stroke = 1) +
  aes(color = sex,
      indicator = sex) +
  geom_lm_indicator() +
* geom_lm_indicator_conf_int()
```
]
 
.panel2-cats-auto[
![](penguins_presentation_ggols_files/figure-html/cats_auto_09_output-1.png)
]

---
count: false

```r
ma206data::chap10_CatJumpingFull %>%
  mutate(sex = case_when(sex_0_f_1_m == 0 ~ "Female",
                         sex_0_f_1_m == 1 ~ "Male")) %>%
  mutate(sex = factor(sex)) %>%
  ggplot() +
  aes(y = muscle_mass_g,
      x = body_mass_g) +
  geom_point(shape = 21, fill = "white", size = 1,
             stroke = 1) +
  aes(color = sex,
      indicator = sex) +
  geom_lm_indicator() +
  geom_lm_indicator_conf_int() +
* geom_lm_indicator_formula()
```
]
 
.panel2-cats-auto[
![](penguins_presentation_ggols_files/figure-html/cats_auto_10_output-1.png)
]

---
count: false

```r
ma206data::chap10_CatJumpingFull %>%
  mutate(sex = case_when(sex_0_f_1_m == 0 ~ "Female",
                         sex_0_f_1_m == 1 ~ "Male")) %>%
  mutate(sex = factor(sex)) %>%
  ggplot() +
  aes(y = muscle_mass_g,
      x = body_mass_g) +
  geom_point(shape = 21, fill = "white", size = 1,
             stroke = 1) +
  aes(color = sex,
      indicator = sex) +
  geom_lm_indicator() +
  geom_lm_indicator_conf_int() +
  geom_lm_indicator_formula() +
* labs(title = "Cats!")
```
]
 
.panel2-cats-auto[
![](penguins_presentation_ggols_files/figure-html/cats_auto_11_output-1.png)
]

---
count: false

```r
ma206data::chap10_CatJumpingFull %>%
  mutate(sex = case_when(sex_0_f_1_m == 0 ~ "Female",
                         sex_0_f_1_m == 1 ~ "Male")) %>%
  mutate(sex = factor(sex)) %>%
  ggplot() +
  aes(y = muscle_mass_g,
      x = body_mass_g) +
  geom_point(shape = 21, fill = "white", size = 1,
             stroke = 1) +
  aes(color = sex,
      indicator = sex) +
  geom_lm_indicator() +
  geom_lm_indicator_conf_int() +
  geom_lm_indicator_formula() +
  labs(title = "Cats!") +
* geom_lm_indicator_fitted(alpha = .2)
```
]
 
.panel2-cats-auto[
![](penguins_presentation_ggols_files/figure-html/cats_auto_12_output-1.png)
]

---
count: false

```r
ma206data::chap10_CatJumpingFull %>%
  mutate(sex = case_when(sex_0_f_1_m == 0 ~ "Female",
                         sex_0_f_1_m == 1 ~ "Male")) %>%
  mutate(sex = factor(sex)) %>%
  ggplot() +
  aes(y = muscle_mass_g,
      x = body_mass_g) +
  geom_point(shape = 21, fill = "white", size = 1,
             stroke = 1) +
  aes(color = sex,
      indicator = sex) +
  geom_lm_indicator() +
  geom_lm_indicator_conf_int() +
  geom_lm_indicator_formula() +
  labs(title = "Cats!") +
  geom_lm_indicator_fitted(alpha = .2) +
* geom_lm_indicator_residuals(alpha = .2)
```
]
 
.panel2-cats-auto[
![](penguins_presentation_ggols_files/figure-html/cats_auto_13_output-1.png)
]

---
count: false

```r
ma206data::chap10_CatJumpingFull %>%
  mutate(sex = case_when(sex_0_f_1_m == 0 ~ "Female",
                         sex_0_f_1_m == 1 ~ "Male")) %>%
  mutate(sex = factor(sex)) %>%
  ggplot() +
  aes(y = muscle_mass_g,
      x = body_mass_g) +
  geom_point(shape = 21, fill = "white", size = 1,
             stroke = 1) +
  aes(color = sex,
      indicator = sex) +
  geom_lm_indicator() +
  geom_lm_indicator_conf_int() +
  geom_lm_indicator_formula() +
  labs(title = "Cats!") +
  geom_lm_indicator_fitted(alpha = .2) +
  geom_lm_indicator_residuals(alpha = .2) +
* geom_lm_indicator_intercept()
```
]
 
.panel2-cats-auto[
![](penguins_presentation_ggols_files/figure-html/cats_auto_14_output-1.png)
]

---
count: false

```r
ma206data::chap10_CatJumpingFull %>%
  mutate(sex = case_when(sex_0_f_1_m == 0 ~ "Female",
                         sex_0_f_1_m == 1 ~ "Male")) %>%
  mutate(sex = factor(sex)) %>%
  ggplot() +
  aes(y = muscle_mass_g,
      x = body_mass_g) +
  geom_point(shape = 21, fill = "white", size = 1,
             stroke = 1) +
  aes(color = sex,
      indicator = sex) +
  geom_lm_indicator() +
  geom_lm_indicator_conf_int() +
  geom_lm_indicator_formula() +
  labs(title = "Cats!") +
  geom_lm_indicator_fitted(alpha = .2) +
  geom_lm_indicator_residuals(alpha = .2) +
  geom_lm_indicator_intercept() +
* geom_lm_indicator_intercept_label(hjust = -.1)
```
]
 
.panel2-cats-auto[
![](penguins_presentation_ggols_files/figure-html/cats_auto_15_output-1.png)
]

---
count: false

```r
ma206data::chap10_CatJumpingFull %>%
  mutate(sex = case_when(sex_0_f_1_m == 0 ~ "Female",
                         sex_0_f_1_m == 1 ~ "Male")) %>%
  mutate(sex = factor(sex)) %>%
  ggplot() +
  aes(y = muscle_mass_g,
      x = body_mass_g) +
  geom_point(shape = 21, fill = "white", size = 1,
             stroke = 1) +
  aes(color = sex,
      indicator = sex) +
  geom_lm_indicator() +
  geom_lm_indicator_conf_int() +
  geom_lm_indicator_formula() +
  labs(title = "Cats!") +
  geom_lm_indicator_fitted(alpha = .2) +
  geom_lm_indicator_residuals(alpha = .2) +
  geom_lm_indicator_intercept() +
  geom_lm_indicator_intercept_label(hjust = -.1)
```
]
 
.panel2-cats-auto[
![](penguins_presentation_ggols_files/figure-html/cats_auto_16_output-1.png)
]

---

```r
*library(NHANES)
```
]
 
.panel2-nhanes-auto[

]

---
count: false

```r
library(NHANES)

*set.seed(123985)
```
]
 
.panel2-nhanes-auto[

]

---
count: false

```r
library(NHANES)

set.seed(123985)
*ggplot(data = NHANES)
```
]
 
.panel2-nhanes-auto[
![](penguins_presentation_ggols_files/figure-html/nhanes_auto_03_output-1.png)
]

---
count: false

```r
library(NHANES)

set.seed(123985)
ggplot(data = NHANES) +
* aes(y = Pulse,
*     x = Age)
```
]
 
.panel2-nhanes-auto[
![](penguins_presentation_ggols_files/figure-html/nhanes_auto_04_output-1.png)
]

---
count: false

```r
library(NHANES)

set.seed(123985)
ggplot(data = NHANES) +
  aes(y = Pulse,
      x = Age) +
* geom_point(alpha = .05)
```
]
 
.panel2-nhanes-auto[
![](penguins_presentation_ggols_files/figure-html/nhanes_auto_05_output-1.png)
]

---
count: false

```r
library(NHANES)

set.seed(123985)
ggplot(data = NHANES) +
  aes(y = Pulse,
      x = Age) +
  geom_point(alpha = .05) +
* geom_jitter(data = . %>%
*              slice_sample(prop = .1),
*            shape = 21, fill = "white",
*            height = .25, width = 0)
```
]
 
.panel2-nhanes-auto[
![](penguins_presentation_ggols_files/figure-html/nhanes_auto_06_output-1.png)
]

---
count: false

```r
library(NHANES)

set.seed(123985)
ggplot(data = NHANES) +
  aes(y = Pulse,
      x = Age) +
  geom_point(alpha = .05) +
  geom_jitter(data = . %>%
               slice_sample(prop = .1),
             shape = 21, fill = "white",
             height = .25, width = 0) +
* aes(color = SleepTrouble, indicator = SleepTrouble)
```
]
 
.panel2-nhanes-auto[
![](penguins_presentation_ggols_files/figure-html/nhanes_auto_07_output-1.png)
]

---
count: false

```r
library(NHANES)

---
count: false

```r
library(NHANES)

set.seed(123985)
ggplot(data = NHANES) +
  aes(y = Pulse,
      x = Age) +
  geom_point(alpha = .05) +
  geom_jitter(data = . %>%
               slice_sample(prop = .1),
             shape = 21, fill = "white",
             height = .25, width = 0) +
  aes(color = SleepTrouble, indicator = SleepTrouble)  +
  geom_lm_interaction() +
* geom_lm_interaction_conf_int()
```
]
 
.panel2-nhanes-auto[
![](penguins_presentation_ggols_files/figure-html/nhanes_auto_09_output-1.png)
]

---
count: false

```r
library(NHANES)

set.seed(123985)
ggplot(data = NHANES) +
  aes(y = Pulse,
      x = Age) +
  geom_point(alpha = .05) +
  geom_jitter(data = . %>%
               slice_sample(prop = .1),
             shape = 21, fill = "white",
             height = .25, width = 0) +
  aes(color = SleepTrouble, indicator = SleepTrouble)  +
  geom_lm_interaction() +
  geom_lm_interaction_conf_int() +
* geom_lm_interaction_formula()
```
]
 
.panel2-nhanes-auto[
![](penguins_presentation_ggols_files/figure-html/nhanes_auto_10_output-1.png)
]

---
count: false

```r
library(NHANES)

set.seed(123985)
ggplot(data = NHANES) +
  aes(y = Pulse,
      x = Age) +
  geom_point(alpha = .05) +
  geom_jitter(data = . %>%
               slice_sample(prop = .1),
             shape = 21, fill = "white",
             height = .25, width = 0) +
  aes(color = SleepTrouble, indicator = SleepTrouble)  +
  geom_lm_interaction() +
  geom_lm_interaction_conf_int() +
  geom_lm_interaction_formula() +
* labs(title = "Pulse!")
```
]
 
.panel2-nhanes-auto[
![](penguins_presentation_ggols_files/figure-html/nhanes_auto_11_output-1.png)
]

---
count: false

```r
library(NHANES)

set.seed(123985)
ggplot(data = NHANES) +
  aes(y = Pulse,
      x = Age) +
  geom_point(alpha = .05) +
  geom_jitter(data = . %>%
               slice_sample(prop = .1),
             shape = 21, fill = "white",
             height = .25, width = 0) +
  aes(color = SleepTrouble, indicator = SleepTrouble)  +
  geom_lm_interaction() +
  geom_lm_interaction_conf_int() +
  geom_lm_interaction_formula() +
  labs(title = "Pulse!") +
* geom_lm_interaction_intercept()
```
]
 
.panel2-nhanes-auto[
![](penguins_presentation_ggols_files/figure-html/nhanes_auto_12_output-1.png)
]

---
count: false

```r
library(NHANES)

set.seed(123985)
ggplot(data = NHANES) +
  aes(y = Pulse,
      x = Age) +
  geom_point(alpha = .05) +
  geom_jitter(data = . %>%
               slice_sample(prop = .1),
             shape = 21, fill = "white",
             height = .25, width = 0) +
  aes(color = SleepTrouble, indicator = SleepTrouble)  +
  geom_lm_interaction() +
  geom_lm_interaction_conf_int() +
  geom_lm_interaction_formula() +
  labs(title = "Pulse!") +
  geom_lm_interaction_intercept() +
* geom_lm_interaction_rsquared()
```
]
 
.panel2-nhanes-auto[
![](penguins_presentation_ggols_files/figure-html/nhanes_auto_13_output-1.png)
]

---
count: false

```r
library(NHANES)

set.seed(123985)
ggplot(data = NHANES) +
  aes(y = Pulse,
      x = Age) +
  geom_point(alpha = .05) +
  geom_jitter(data = . %>%
               slice_sample(prop = .1),
             shape = 21, fill = "white",
             height = .25, width = 0) +
  aes(color = SleepTrouble, indicator = SleepTrouble)  +
  geom_lm_interaction() +
  geom_lm_interaction_conf_int() +
  geom_lm_interaction_formula() +
  labs(title = "Pulse!") +
  geom_lm_interaction_intercept() +
  geom_lm_interaction_rsquared() +
* coord_cartesian(ylim = c(65,85))
```
]
 
.panel2-nhanes-auto[
![](penguins_presentation_ggols_files/figure-html/nhanes_auto_14_output-1.png)
]

---
count: false

```r
library(NHANES)

set.seed(123985)
ggplot(data = NHANES) +
  aes(y = Pulse,
      x = Age) +
  geom_point(alpha = .05) +
  geom_jitter(data = . %>%
               slice_sample(prop = .1),
             shape = 21, fill = "white",
             height = .25, width = 0) +
  aes(color = SleepTrouble, indicator = SleepTrouble)  +
  geom_lm_interaction() +
  geom_lm_interaction_conf_int() +
  geom_lm_interaction_formula() +
  labs(title = "Pulse!") +
  geom_lm_interaction_intercept() +
  geom_lm_interaction_rsquared() +
  coord_cartesian(ylim = c(65,85))
```
]
 
.panel2-nhanes-auto[
![](penguins_presentation_ggols_files/figure-html/nhanes_auto_15_output-1.png)
]

@media print {
  .has-continuation {
    display: block;
  }
}

</style>