Open the Required Packages

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

Import & Name Dataset

DatasetB2 <- read_excel("D:/SLU/AdvAppliedAnalytics/DatasetB2.xlsx")

Create a Contingency Table

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

Create a Bar Chart

ggplot(DatasetB2, aes(x = StudentType, fill = PetOwnership)) +
  geom_bar(position = "dodge") +                 
  labs(
    x = "StudentType",
    y = "Frequency",
    title = "Pet Ownership by Student"
  ) +
  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

The p-value is 0.841 which is greater than 0.05, so the result is not statistically significant.

Report the Results

The Chi-Square Test of Independence indicated there was not a significant association between Student Type and Pet Ownership, χ²(1) = 0.04, p = .841 which is greater than 0.05, so the result is not statistically significant.