library(readxl)
> A4Q1 <- read_excel("C:/Users/eboni/Downloads/A4Q1.xlsx")
> View(A4Q1)
> 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 if there was a difference between the observed ice cream flavor frequencies and the expected frequencies.
> #The results showed that there [was / was not] a difference between the observed and expected frequencies, χ²(3) = 41.6, p = .001.
> # The difference was moderate (Cohen's W = .41).