```{r} observed <- table(A4Q1\(flavor) observed barplot(observed, main = "Ice Cream flavor", xlab = "Ice Cream flavor", ylab = "frequency", col = rainbow(length(observed))) expected <- c(.20, .20, .20, .40) chi_result <- chisq.test(x = observed, p = expected) chi_result w <- sqrt(as.numeric(chi_result\)statistic) / sum(observed)) w

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 a difference between the observed and expected frequencies, x²(3) = 41.6, p = p > .05.

The difference was moderate (Cohen’s W = .40). ```