Responses to a post on the correlation between country-average IQ and responding yes to a question on if religion matters are inversely correlated, but not strongly so, prompted me to dig up a more significant issue, the relationship between religiosity and inequality, as measured by the Gini coefficient.

The correlation is quite high, at about .7, although this really says nothing about the cause, if religious countries tend toward inequality because of general tendencies, or if inequality drives people to religion, as a salve against suffering. In truth, they could both be reflective of some other aspect of a country, and not in any way causative.

Example Code

Example Results

Sample Data

The correlation is quite high, at about .7, although this really says nothing about the cause, if religious countries tend toward inequality because of general tendencies, or if inequality drives people to religion, as a salve against suffering. In truth, they could both be reflective of some other aspect of a country, and not in any way causative.

Example Code

```
# Correlations on ReligionMatters and Gini Coeficients
oecdData <- read.table("OECD - Quality of Life.csv", header = TRUE, sep = ",")
#names(oecdData)
religionMattersVector <- oecdData$ReligionMatters
giniVector <- oecdData$Gini
cor.test(giniVector, religionMattersVector)
lm2 <- lm(giniVector ~ religionMattersVector)
summary(lm2)
# Plot the chart.
plot(giniVector, religionMattersVector, col = "blue", main = "Gini Coefficient ~ Religion Matters Vector"
, abline(lm(religionMattersVector ~ giniVector)), xlab = "Religion Matters", ylab = "Gini")
```

Example Results

```
Pearson's product-moment correlation
data: giniVector and religionMattersVector
t = 4.4676, df = 20, p-value = 0.0002359
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
0.4061694 0.8693247
sample estimates:
cor
0.7067507
Call:
lm(formula = giniVector ~ religionMattersVector)
Residuals:
Min 1Q Median 3Q Max
-5.400 -2.174 -1.629 1.626 7.054
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 23.597 1.989 11.866 1.66e-10 ***
religionMattersVector 19.810 4.434 4.468 0.000236 ***
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 3.513 on 20 degrees of freedom
(2 observations deleted due to missingness)
Multiple R-squared: 0.4995, Adjusted R-squared: 0.4745
F-statistic: 19.96 on 1 and 20 DF, p-value: 0.0002359
```

Sample Data