Chi-Square Goodness-of-Fit Test Research Question: Do students prefer tea, coffee, soda and water equally?

Step 1: Install Required Packages install.packages(“readxl”) install.packages(“ggplot2”) install.packages(“rcompanion”)

Step 2: Open Installed Packages

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

Step 3: Import and Name Dataset

DatasetA2 <- read_excel("C:/Users/srina/OneDrive/Documents/Madhu Master's/Applied Analytics/Assignment 5/DatasetA2.xlsx")

Step 4: Create Frequency Table

table(DatasetA2$FavoriteDrink)
## 
## Coffee   Soda    Tea  Water 
##     26     29     28     17

Step 5: Create Bar Chart

ggplot(DatasetA2, aes(x = FavoriteDrink, fill = FavoriteDrink)) +
  geom_bar() +
  labs(x = "Favorite Drink", 
       y = "Frequency",
       title = "Distribution of FavoriteDrink") +
  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"   
  )

Step 6: Conduct Chi-Square Goodness-of-Fit Test

observed <- table(DatasetA2$FavoriteDrink)
expected <- c(1/4, 1/4, 1/4, 1/4)
chisq.test(x = observed, p = expected)
## 
##  Chi-squared test for given probabilities
## 
## data:  observed
## X-squared = 3.6, df = 3, p-value = 0.308

A chi-square goodness-of-fit test indicated that the observed frequencies were not significantly different from the expected frequencies, χ²(3) = 3.60, p = .308. The association between the observed and expected distributions was weak (Cohen’s W = .14).