B2 Markdown

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

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

tab <- table(DatasetB2$StudentType, DatasetB2$PetOwnership)
tab

##                
##                 No Yes
##   Domestic      27  25
##   International 23  25

ggplot(DatasetB2, aes(x = StudentType, fill = PetOwnership)) +
  geom_bar(position = "dodge") +
  labs(
    x = "Student Type",
    y = "Frequency",
    title = "Pet Ownership by Student Type"
  ) +
  theme(
    text = element_text(size = 14),
    axis.title = element_text(size = 14),
    axis.text = element_text(size = 14),
    plot.title = element_text(size = 14)
  )

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 Chi-Square Test of Independence indicated there was not a significant association between student type and pet ownership, χ²(1) = 0.040064, p = .8414. Hence, the Cohen's W (Effect Size) was not calculated.