library(readxl)
library(rcompanion)
library(ggplot2)
A4Q2 <- read_excel("C:/Users/peter/Desktop/SLU/AA 5221 Applied Analytics & Methods/Week 4/A4Q2.xlsx")
nationality <- table(A4Q2$status, A4Q2$scholarship)
nationality

##                
##                   0   1
##   Domestic       39 111
##   International 118  32

barplot(nationality,
        beside = TRUE,
        col = rainbow(nrow(nationality)),
        legend = rownames(nationality))

chi_result <- chisq.test(nationality)
chi_result

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  nationality
## X-squared = 81.297, df = 1, p-value < 2.2e-16

rcompanion::cramerV(nationality)

## Cramer V 
##   0.5272

# A Chi-Square Test of Independence was conducted to determine if there was an association between Variable 1 and Variable 2.
# The results showed that there was an association between the two variables, χ²(1) = 81.30, p = 2.2e-16.
# The association was large, (Cramer's V = 0.53).