William Farr’s Observations on Cholera in London

Setting up R Packages

library(tidyverse)
library(mosaic)
library(skimr)
library(ggformula)
library(GGally)

Introduction

John Snow’s contention that cholera was principally spread by water was not accepted in the 1850s by the medical elite. The consequence of rejection was that hundreds in the UK continued to die. William Farr, who founded the science of epidemiology, tried to examine if there were other causes that led to cholera. He had concluded that the available data not only supported miasma (spread via atmospheric vapours) but also indicated that there was an underlying ‘natural law’ linking infection with cholera inversely to elevation above high water. The data is available on Vincent Arel-Bundock’s website, and is part of the HistData package from Michael Friendly, UC Davis.

Read the Data

Cholera <- read_csv("https://vincentarelbundock.github.io/Rdatasets/csv/HistData/Cholera.csv")
Cholera

ABCDEFGHIJ0123456789

rownames <dbl>	district <chr>	cholera_drate <dbl>	cholera_deaths <dbl>	popn <dbl>	elevation <dbl>	region <chr>
1	Newington	144	907	63074	-2	Kent
2	Rotherhithe	205	352	17208	0	Kent
3	Bermondsey	164	836	50900	0	Kent
4	St George Southwark	161	734	45500	0	Kent
5	St Olave	181	349	19278	2	Kent
6	St Saviour	153	539	35227	2	Kent
7	Westminster	68	437	64109	2	West
8	Lambeth	120	1618	134768	3	Kent
9	Camberwell	97	504	51704	4	Kent
10	Greenwich	75	718	95954	8	Kent

Data Dictionary

Quantitative Variables

Write in.

Qualitative Variables

Write in.

Observations

Write in.

Research Question

Note

Write in! Look at the charts below!

Analyse/Transform the Data

```{r}
#| label: data-preprocessing
#
# Write in your code here
# to prepare this data as shown below
# to generate the plot that follows
```

Plot the Data

Tasks and Discussion

Complete the Data Dictionary.
Select and Transform the variables as needed.
Look at Plot 1. Would you agree based on this chart that William Farr was right in believing that elevation was a good predictor for cholera deaths? Justify.
What is the nature of the relationship between Cholera Deaths and Elevation?
Look at Plot 2. What kind of plot is it? What is the relationship here between Elevation and Cholera Death Rate?
Based on this graph, would you agree that Elevation is a predictor for Cholera Deaths? Justify.
Is the relationship you found between Cholera Deaths and Elevation also found in Plot 1? Justify.
Look at Plot 3. Would you guess that there could be another predictor for Cholera Deaths? What could that Predictor be? Justify.