library(readxl)
library(ggplot2)
library(rcompanion)
A5Q2 <- read_excel("/Users/murphy/Downloads/A5Q2.xlsx")
MyTable <- table(A5Q2$nationality, A5Q2$scholarship_awarded)
MyTable
##                
##                   0   1
##   Domestic       39 111
##   International 118  32
            0   1

Domestic 39 111 International 118 32

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

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

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

Cramer V 0.5272

A Chi-Square Test of Independence was conducted to determine if there was an association between a student nationality (domestic versus international) and whether or not they have a scholarship (yes versus no). The results showed that there was an association between the two variables, χ²(1) = 81.30, p < .001. The association was strong, (Cramer’s V = 0.53).