Plot Arbuthnot’s data with ggplot2

John Arbuthnot (1710) gathered data on the ratios of male to female christenings in London from 1629-1710 to carry out the first known significance test, comparing observed data to a null hypothesis. The data for these 81 years showed that in every year there were more male than female christenings. Let’s make a plot for him.

Load the data & ggplot2

library(ggplot2) # Plots Using the Grammar of Graphics  
data(Arbuthnot, package="HistData")
head(Arbuthnot)

##   Year Males Females Plague Mortality Ratio Total
## 1 1629  5218    4683      0      8771 1.114 9.901
## 2 1630  4858    4457   1317     10554 1.090 9.315
## 3 1631  4422    4102    274      8562 1.078 8.524
## 4 1632  4994    4590      8      9535 1.088 9.584
## 5 1633  5158    4839      0      8393 1.066 9.997
## 6 1634  5035    4820      1     10400 1.045 9.855

Basic plot: points & lines

I assign the initial plot to a variable, arbuthplot, so I can add additional graphical elements to it. I also expand the Y axis limits a bit to allow for annotations.

arbuthplot <-
ggplot(Arbuthnot, aes(x=Year, y=Ratio)) +
  ylim(1, 1.20) + 
  ylab("Sex Ratio (M/F)") +
  geom_point(pch=16, size=2) +
  geom_line(color="gray") 
arbuthplot

Add smooths

He might have been interested in whether there was any trend over time. We can add a linear regression line and loess smooth using geom_smooth.

arbuthplot +
  geom_smooth(method="loess", color="blue", fill="blue", alpha=0.2) +
  geom_smooth(method="lm", color="darkgreen", se=FALSE)  

Add reference line, annotations and change the theme

To highlight that a sex ratio = 1.0 is the null hypothesis, add a thick red line at that value. Instead of a plot title outside the plot frame, you can add text annotations inside.

arbuthplot +
  geom_smooth(method="loess", color="blue", fill="blue", alpha=0.2) +
  geom_smooth(method="lm", color="darkgreen", se=FALSE) +
  geom_hline(yintercept=1, color="red", size=2) +
  annotate("text", x=1645, y=1.01, label="Males = Females", color="red", size=5) +
  annotate("text", x=1680, y=1.19, 
           label="Arbuthnot's data on the\nMale / Female Sex Ratio", size=5.5) +
  theme_bw() + 
  theme(text = element_text(size = 16))