Open the Installed Packages

library(readxl)
library(ggplot2)

Import and Name Dataset

DatasetA2 <- read_excel("C:/Users/DELL/Documents/Applied Analytics/Assignment5/DatasetA2.xlsx")

Create a Frequency Table

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

Create a Bar Chart

ggplot(DatasetA2, aes(x = FavoriteDrink, fill = FavoriteDrink)) +
  geom_bar() +
  labs(
    x = "Favorite Drink",
    y = "Frequency",
    title = "Distribution of Student's Favorite Drink"
  ) +
  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 Goodness-of-Fit Test

observed <- c(26, 29, 28, 17) 
expected <- c(0.25, 0.25, 0.25, 0.25)
chisq.test(x = observed, p = expected)
## 
##  Chi-squared test for given probabilities
## 
## data:  observed
## X-squared = 3.6, df = 3, p-value = 0.308

Interpret and Report the Results

A chi-square goodness-of-fit test indicated that the observed frequencies were different from the expected frequencies, χ²(3) = 3.6, p = 0.308. The Cohen’s W (Effect Size) was not calculated because the p-value is not statistically significant.