library(readxl)

A4Q1 <- read_excel("C:/Users/eboni/Downloads/A4Q1.xlsx")

observed <- table(A4Q1$flavor)
observed

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

barplot(observed,
        main = "Ice Cream Purchases",
        xlab = "Flavor",
        ylab = "Count",
        col = rainbow(length(observed)))

expected <- c(.2, .2, .2, .4)

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

w <- sqrt(as.numeric(chi_result$statistic) / sum(observed))
w

## [1] 0.4079216

A Chi-Square Goodness-of-Fit Test was conducted to determine whether the observed flavor frequencies differed from the expected frequencies. The results showed a statistically significant difference, χ²(3) = 41.60, p < .001. The difference was moderate, Cohen’s w = .41.