library(readxl)
library(ggplot2)
library(rcompanion)
luigi<- read_excel("D:/Vedant Work/SLU/Spring Sem (Jan to May 2026)/Applied Analytics/Assignment 5/luigi.xlsx")
colnames(luigi)
## [1] "studentid"    "studenttype"  "petownership"

deploying table for refrence

tab<- table(luigi$studenttype,  luigi$petownership)
tab
##                
##                 No Yes
##   Domestic      27  25
##   International 23  25

displaying bar chart for clarity

ggplot(luigi,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" 
    )

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 was conducted to determine whether there is a relationship between student type and pet ownership. The results indicated that there was no statistically significant association between student type and pet ownership,
χ²(1) = 0.040, p = 0.8414. Since the p-value is greater than 0.05, we fail to reject the null hypothesis. Therefore, student type and pet ownership appear to be independent. Because the result was not statistically significant, Cramer’s V was not calculated.