### Chi-Square in R on by State Politics (Red/Blue) and Income (Higher/Lower)

This is a significant result, but instead of a logistic regression looking at the income average per state and the likelihood of being a Democratic state, it uses Chi-Square. Interpreting this is pretty straightforward, in that liberal states typically have cities and people that earn more money. When using adjusted incomes, by cost of living, this difference disappears.

Example Code
``````
# R - Chi Square
rm(list = ls())

# Create vectors
affluence.median <- median(stateData\$Y2014, na.rm = TRUE)
affluence.v <- ifelse(stateData\$Y2014 > affluence.median, 1, 0)
liberal.v <- stateData\$Liberal

# Solve
pol.Data = table(liberal.v, affluence.v)
result <- chisq.test(pol.Data)
print(result)
print(pol.Data)
``````

Example Results
``````
Pearson's Chi-squared test with Yates' continuity correction

data: pol.Data
X-squared = 12.672, df = 1, p-value = 0.0003711

> print(pol.Data)
+
affluence.v
liberal.v     0  1
0  22 7
1  4 16
``````

Sample Data