library(readxl)
library(rcompanion)
library(ggplot2)
A4Q2 <- read_excel("C:/Users/giuli/OneDrive - Saint Louis University/A4Q2.xlsx")
table(A4Q2$status, A4Q2$scholarship)

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

Table2 <- table(A4Q2$status, A4Q2$scholarship)
Table2

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

barplot(Table2,
beside = TRUE,
col = rainbow(nrow(Table2)),
legend = rownames(Table2))

chi_result <- chisq.test(Table2)

chi_result

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  Table2
## X-squared = 81.297, df = 1, p-value < 2.2e-16

rcompanion::cramerV(Table2)

## 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(df) = 75.62, p = 2.663e-16

# The association was large, (Cramer's V = 0.53).