DatasetB2

Open the Installed Packages

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

Import and Name Dataset

DatasetB2 <- read_excel("C:/Users/cniti/Documents/AA-5221 Applied Analytics/DatasetB2.xlsx")

Create a Contingency Table

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

Create Bar Charts

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

Cramer’s V (Effect Size)

cramerV(tab)

## Cramer V 
##  0.04003

The Chi-Square Test of Independence indicated there was/ was not a significant association between gender and voting behavior, χ²(1) = 0.040, p = .8414.The association between the two variables was moderate (Cramer’s V = 0.04003).