library(readxl)
library(rcompanion)
library(ggplot2)
A4Q2 <- read_excel("C:/Users/onhau01/OneDrive - Saint Louis University/AA 5221/Assignment 4/A4Q2.xlsx")
table(A4Q2$status, A4Q2$scholarship)

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

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

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

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

#Conduct a Chi-Square Test of Independence

chi_result <- chisq.test(uni_student_table)

chi_result

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

#Calculate Cramer's V

rcompanion::cramerV(uni_student_table)

## Cramer V 
##   0.5272

# A Chi-Square Test of Independence was conducted to determine if there was an association between status and scholarship.

# The results showed that there was  an association between the two variables, χ²(1) = 81.30, p < .001.

# The association was large, (Cramer's V = .0.53).