Open the Required Packages

library(readxl)
## Warning: package 'readxl' was built under R version 4.6.1
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.6.1
library(rcompanion)
## Warning: package 'rcompanion' was built under R version 4.6.1

Import & Name Dataset

A5Q2 <- read_excel("C:/Users/rteno/OneDrive - Saint Louis University/AA 5221/AA 5221-11_Assignment 5/A5Q2.xlsx")

Create a Contingency Table

MyTable <- table(A5Q2$nationality,
                 A5Q2$scholarship_awarded)
MyTable
##                
##                   0   1
##   Domestic       39 111
##   International 118  32

Create a bar chart

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

Conduct the Chi-Square Test of Independence

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

Cramer’s V (Effect Size)

rcompanion::cramerV(MyTable)
## Cramer V 
##   0.5272

Interpret and Report the Results

# A Chi-Square Test of Independence was conducted to determine if there was an association between student nationality and whether or not they had a scholarship.
# 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).