Open the Installed Packages

library(readxl) 
library(ggplot2) 
library(rcompanion)

Import and Name Dataset

DatasetB2 <- read_excel("/Users/poojithareddybavanam/Desktop/DatasetB2.xlsx")

Import and Name Dataset

tab <- table(DatasetB2$StudentType, DatasetB2$PetOwnership)
tab
##                
##                 No Yes
##   Domestic      27  25
##   International 23  25

Create Bar Charts

ggplot(DatasetB2, aes(x = StudentType, fill = PetOwnership)) +
  geom_bar(position = "dodge") +               
  labs(
    x = "StudentType",
    y = "Frequency",
    title = "PetOwnership by StudentType"
  ) +
  theme(
    text = element_text(size = 14),
    axis.title = element_text(size = 14),
    axis.text = element_text(size = 14),
    plot.title = element_text(size = 14),
    legend.position = "none"
  )

Conduct the Chi-Square Test of Independence

chisq.test(tab)
## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  tab
## X-squared = 0.040064, df = 1, p-value = 0.8414

Cramer’s V (Effect Size)

cramerV(tab)
## Cramer V 
##  0.04003

The Chi-Square Test of Independence indicated there was not a significant association between StudentID and FavoriteDrink, χ²(297) = 300.00, p = .440. The association between the two variables was weak (Cramer’s V = .04).