library(readxl)
library(ggplot2)
library(rcompanion)
A4Q2 <- read_excel("C:/Users/hp/Downloads/A4Q2.xlsx")
MyTable <- table(A4Q2$scholarship, A4Q2$status)
MyTable

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

barplot(
  MyTable,
  beside = TRUE,
  col = rainbow(nrow(MyTable)),
  legend.text = rownames(MyTable)
)

chi_result <- chisq.test(MyTable) 
chi_result

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

rcompanion::cramerV(MyTable)

## Cramer V 
##   0.5272

# A Chi-Square Test of Independence was conducted to determine if there was an association between Scholarship allocation and Status. 
# The results showed that there was an association between the two variables, χ²(1) = 81.297, p < 0.001 
# The association was strong, (Cramer's V = .5272).