README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%",
  fig.retina = 2
)
library(tidyverse)
library(patchwork)
```
# Dataforsocialscience

The goal of `dataforsocialscience` is to bundle a set of data sets that are useful for teaching statistics in a social science field.

## Installation

You can install the current version of dataforsocialscience from github as follows:

```r
if(!require(remotes)){
  install.packages(remotes)
} 
remotes::install_github("statisticsforsocialscience/dataforsocialscience")
```

## Example data sets

These are the datasets contained in this package.

### Robot care

```{r example}
library(tidyverse)
library(dataforsocialscience)

robo_care %>% names()
robo_care %>% 
  ggplot() + 
  aes(cse, y = robo_bed, color = gender) + 
  geom_jitter(width = 0.2, height = 0.2, alpha = 0.8) +
  geom_smooth(method = "lm") +
  scale_x_continuous("Computer Self-Efficacy", breaks = 1:6) +
  scale_y_continuous("Would you accept that a robot brings you to bed?", breaks = 1:6) +
  labs(color = "Gender")

```


### Phone usage
```{r example_phone}
data("anova_phone")
ggplot(anova_phone) + 
  aes(phone, whatsapp, color = phone) +
  geom_point() +
  ggtitle("Sum of Squares within") +
  scale_y_continuous("Whatsapp messages per day", breaks = 1:10) +
  geom_line(data = data.frame(x = c(0.6,1.4), y = c(2.0,2.0)), aes(x,y), inherit.aes = FALSE, size = 1, color = 2) +
  geom_label(label = "M1", x = 1.3, y = 2.3, inherit.aes = FALSE, size = 6) +
  geom_line(data = data.frame(x = c(1.6,2.4), y = c(5.0,5.0)), aes(x, y), inherit.aes = FALSE, size = 1, color = 3) +
  geom_label(label = "M2", x = 2.3, y = 5.3, inherit.aes = FALSE, size = 6) +
  geom_line(data = data.frame(x = c(2.6,3.4), y = c(8.0,8.0)), aes(x,y), inherit.aes = FALSE, size = 1, color = 4) +
  geom_label(label = "M3", x = 3.3, y = 8.3, inherit.aes = FALSE, size = 6)

```

### Simpson Paradox

```{r simpson}
p1 <- simpson_paradox %>% 
  ggplot() + 
  aes(x = V2, y = V1, color = group) + 
  geom_point() + 
  geom_smooth(method = "lm")

p2 <- simpson_paradox %>% 
  ggplot() + 
  aes(x = V2, y = V1) + 
  geom_point() + 
  geom_smooth(method = "lm")

p2 + p1 + patchwork::plot_annotation(title = "Demonstrating the Simpson Paradox")
```