library(readxl)
A4Q1 <- read_excel("C:/Users/onhau01/Desktop/R-Revision/A4Q1.xlsx")

#Create and View a Frequency Table
table(A4Q1$flavor)

## 
##  Chocolate      Mango Strawberry    Vanilla 
##         87         32         57         74

observed <-table(A4Q1$flavor)

#Create a Bar Chart
barplot(observed,
main = "flavor",
xlab = "flavor",
ylab = "Count",
col = rainbow(length(observed)))

#Calculate Goodness-of-Fit Test
expected <- c(.20, .20, .20, .40)

chi_result <- chisq.test(x = observed, p = expected)
chi_result

## 
##  Chi-squared test for given probabilities
## 
## data:  observed
## X-squared = 41.6, df = 3, p-value = 4.878e-09

#Calculate the Effect Size (Cohen's W)
w <- sqrt(as.numeric(chi_result$statistic) / sum(observed))
w

## [1] 0.4079216

#Reporting the Results:
# A Chi-Square Goodness-of-Fit test was conducted to determine if there was a difference between the observed [categorical variable] frequencies and the expected frequencies.
# The results showed that there was a difference between the observed and expected frequencies, χ²(3) = 41.6, p < .001.
# The difference was moderate  (Cohen's W = .41.).