Step 1: Import and load necessary packages

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

Step 2: Load the dataset into R environment

datasetA2 <- read_excel("/Users/sarva/Desktop/DatasetA2.xlsx")

Step 3: Creating a frequency table with the provided dataset

table(datasetA2$FavoriteDrink)

## 
## Coffee   Soda    Tea  Water 
##     26     29     28     17

Step 4 : Creating a bar chart

ggplot(datasetA2, aes(x = FavoriteDrink, fill = FavoriteDrink)) +
  geom_bar() +
  labs(
    x = "favorite drink",
    y = "Frequency",
    title = "Distribution of Favourite 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"             
  )

Step 5 : Conduct the Chi Square test of goodness

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

cramerV (observed, correct=FALSE)

A chi-square goodness-of-fit test indicated that the observed frequencies were not different from the expected frequencies, χ²(df) = 3.6, p = 0.308.

Dataset A2

Sarvadnya

2026-02-16

A chi-square goodness-of-fit test indicated that the observed frequencies were not different from the expected frequencies, χ²(df) = 3.6, p = 0.308.