library(readxl)
library(rcompanion)
library(ggplot2)
A4Q2 <- read_excel("C:/Users/DELL/OneDrive - Saint Louis University/AA 5221/Assignment 4/A4Q2.xlsx")
View(A4Q2)
table(A4Q2$status, A4Q2$scholarship)

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

domestic_vs_international <- table(A4Q2$status, A4Q2$scholarship)
domestic_vs_international

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

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

chi_result <- chisq.test(domestic_vs_international)
chi_result

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

# A Chi-Square Test of Independence was conducted to determine if there was an association between student nationality (domestic vs. international) and scholarship status.
#The results showed a statistically significant association between nationality and scholarship status, χ²(1) = 81.30, p < .001.
#The association was large, (Cramer's V = .53).
rcompanion::cramerV(domestic_vs_international)

## Cramer V 
##   0.5272