Chi-Square Test of Independence
library(readxl)
library(ggplot2)
library(rcompanion)
A5Q2 <- read_excel("A5Q2.xlsx")
MyTable <- table(A5Q2$nationality, A5Q2$scholarship_awarded)
MyTable
##
## 0 1
## Domestic 39 111
## International 118 32
barplot(MyTable, beside = TRUE,
col = rainbow(nrow(MyTable)),
legend = 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 student nationality and scholarship status.
# 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 = .53).