Step 1 opening the installed packages

install.packages("readxl") 
## Installing package into 'C:/Users/pavan/AppData/Local/R/win-library/4.5'
## (as 'lib' is unspecified)
## package 'readxl' successfully unpacked and MD5 sums checked
## Warning: cannot remove prior installation of package 'readxl'
## Warning in file.copy(savedcopy, lib, recursive = TRUE): problem copying
## C:\Users\pavan\AppData\Local\R\win-library\4.5\00LOCK\readxl\libs\x64\readxl.dll
## to C:\Users\pavan\AppData\Local\R\win-library\4.5\readxl\libs\x64\readxl.dll:
## Permission denied
## Warning: restored 'readxl'
## 
## The downloaded binary packages are in
##  C:\Users\pavan\AppData\Local\Temp\Rtmp0gQVSb\downloaded_packages
install.packages("ggplot2") 
## Installing package into 'C:/Users/pavan/AppData/Local/R/win-library/4.5'
## (as 'lib' is unspecified)
## package 'ggplot2' successfully unpacked and MD5 sums checked
## 
## The downloaded binary packages are in
##  C:\Users\pavan\AppData\Local\Temp\Rtmp0gQVSb\downloaded_packages
install.packages("rcompanion")
## Installing package into 'C:/Users/pavan/AppData/Local/R/win-library/4.5'
## (as 'lib' is unspecified)
## package 'rcompanion' successfully unpacked and MD5 sums checked
## 
## The downloaded binary packages are in
##  C:\Users\pavan\AppData\Local\Temp\Rtmp0gQVSb\downloaded_packages

Step 2 Open the Required Packages

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

Step 3: Import & Name Dataset

DatasetB2 <- read_excel("C:/Users/pavan/Desktop/DatasetB2.xlsx")

Step 4: Create a Contingency Table

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

Step 5: 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"                 
  )

Step 6: 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

Step 7: Cramer’s V (Effect Size)

cramerV(tab)
## Cramer V 
##  0.04003

Results:The Chi-Square Test of Independence indicated there was not a significant association between Variable A and Variable B,χ²(1) = 0.04, p = .841. The association between the two variables was weak (Cramér’s V = .04).