A5Q1

’’’(R) OBSERVED <- table(A5Q1_1$flavor) OBSERVED Chocolate Mango Strawberry Vanilla 87 32 57 74

barplot(OBSERVED, main = “flavor distribution”, xlab = “flavor”, ylab = “count”, col = rainbow(length(OBSERVED))) expected <- c(.20, .10, .30, .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 flavor frequencies and the expected frequencies.

#The results showed that there was a difference between the observed and expected frequencies, x^2(3) = 121.26, p = 3.57

#The difference was strong, (Cohen’s W = .40).