Introduction

The purpose of this project is to examine whether there is an association between smallpox inoculation and survival outcomes. Smallpox was a deadly disease, and inoculation was an early method used to reduce mortality. Understanding whether inoculation is associated with survival provides insight into the effectiveness of early public health interventions.

The dataset used in this analysis comes from the OpenIntro Statistics data repository. Each observation represents an individual and includes information on whether the individual was inoculated against smallpox and whether they lived or died from the disease. The variables used in this analysis are inoculated and result.

#Data Analysis

In this analysis, exploratory data analysis (EDA) is used to examine the relationship between inoculation status and survival outcomes. Frequency tables, proportions, and bar plots are used to summarize and visualize the data.

smallpox <- read.csv("smallpox.csv")

summary(smallpox)
##     result           inoculated       
##  Length:6224        Length:6224       
##  Class :character   Class :character  
##  Mode  :character   Mode  :character
table(smallpox$inoculated, smallpox$result)
##      
##       died lived
##   no   844  5136
##   yes    6   238
prop.table(table(smallpox$inoculated, smallpox$result), margin = 1)
##      
##             died      lived
##   no  0.14113712 0.85886288
##   yes 0.02459016 0.97540984
ggplot(smallpox, aes(x = inoculated, fill = result)) +
geom_bar(position = "dodge") +
labs(
title = "Survival Outcomes by Smallpox Inoculation Status",
x = "Inoculation Status",
y = "Count",
fill = "Outcome"
)

Conclusion and Future Directions

The results of this analysis suggest that survival outcomes differ between individuals who were inoculated and those who were not. Inoculated individuals appear to have a higher proportion of survival compared to non-inoculated individuals. This finding supports the idea that inoculation was an effective method for reducing mortality from smallpox.

Future research could include formal statistical testing, such as a chi-square test of independence, to assess whether the observed association is statistically significant. Additional variables, such as age or health status, could also be explored if available to better understand factors influencing survival outcomes.

#References

OpenIntro Statistics. Smallpox dataset. https://www.openintro.org/data/index.php?data=smallpox