Assign 5_Q2

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

A5Q2$scholarship_awarded <- as.factor(A5Q2$scholarship_awarded)

ggplot(A5Q2, aes(x = nationality, fill = scholarship_awarded)) +
  geom_bar(position = "dodge")

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

rcompanion::cramerV(MyTable)

## Cramer V 
##   0.5272

# A Chi-Square Test of Independence test 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(1) = 81.3, p < .001.

# The association was strong, (Cramer's V = .53).