Inequality Kills: Correlation, with Graph and Least Square, of Gini Coefficient (Inequality) and Infant Death

At a correlation approaching 0.7, the relationship between infant mortality and inequality is quite high. One can argue causality, but the existence of the relationship, and there are others of varying magnitude, is a powerful indictment:

Example Code

 oecdData <- read.table("OECD - Quality of Life.csv", header = TRUE, sep = ",")  
 gini.v <- oecdData$Gini  
 death.v <- oecdData$InfantDeath  
 cor.test(gini.v, death.v)  
 plot(gini.v, death.v, col = "blue", main = "Infant Death v Gini"
 , abline(lm(death.v ~ gini.v))
 , cex = 1.3, pch = 16, xlab = "Gini", ylab = "Infant Death")  


Example Results

 Pearson's product-moment correlation  
   
 data: gini.v and death.v  
 t = 4.2442, df = 19, p-value = 0.0004387  

 alternative hypothesis: true correlation is not equal to 0  

 95 percent confidence interval:  
  0.3805316 0.8679275  

 sample estimates:  

   cor   
   0.69762   

Example Graph


Sample Data

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