DatasetB2

Open the Required Packages

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

Import & Name Dataset

DatasetB2 <- read_excel("C:/Users/tejas/Downloads/DatasetB2.xlsx")

Create a Contingency Table

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)
  )

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

Interpretation Result

The Chi-Square Test of Independence indicated there was not a significant association between StudentType and PetOwnership, χ²(1) = 0.040064, p = .8414.