’’’{r barplot, include = TRUE} library(readxl) library(ggpubr) library(readxl) A5Q1_1 <- read_excel(“Desktop/AA-5221-22 Applied Analytics & Methods I/A5Q1-1.xlsx”) View(A5Q1_1) observed <- table(A5Q1_1\(flavor) observed barplot(observed, main = "Distribution of Flavors", xlab = "Flavor", ylab = "Count", col = rainbow(length (observed))) expected <- c(.20, .20, .20, .40) chi_result <-chisq.test(x = observed, p = expected) chi_result w <- sqrt(as.numeric(chi_result\)statistic) / sum(observed)) w A Chi-Square Goodness of Fit test was conducted to determine if there was a difference between the observed [flavors] 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 = .4).