A4Q2

library(readxl)
library(rcompanion)
library(ggplot2)

A4Q2 <- read_excel("A4Q2.xlsx")
status_scholarship_table <- table(A4Q2$status, A4Q2$scholarship)
status_scholarship_table

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

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

chi_result <- chisq.test(status_scholarship_table)
chi_result

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

rcompanion::cramerV(status_scholarship_table)

## Cramer V 
##   0.5272

# A Chi-Square Test of Independence was conducted to determine if there was an association between status and scholarship.
# The results showed that there was an association between the two variables, χ²(1) = 81.30, p < .001.
# The association was large (Cramer's V = .53).