library(readxl)
library(rcompanion)
library(ggplot2)
A4Q2 <- read_excel("//apporto.com/dfs/SLU/Users/hannahsmith3_slu/Downloads/A4Q2.xlsx")
table(A4Q2$status, A4Q2$scholarship)

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

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

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

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

chi_result <- chisq.test(Status_Scholarships)
chi_result

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

rcompanion::cramerV(Status_Scholarships)

## Cramer V 
##   0.5272

#A Chi-Square Test of Independence was conducted to determine if there was an association between students' nationality and scholarship status. 
#The results showed that there was an association between the two variables, X^2(1) = <.001
#The association between nationality and scholarship status was large, Cramer's V = .52