library(ggpubr)
A5Q1_1 <- read_excel("Downloads/A5Q1-1.xlsx")
observed <- table(A5Q1_1$flavor)
observed
barplot(observed,
        main = "Flavor",
        xlab = "Flavor",
        ylab = "Count",
        col = rainbow(length(observed)))

expected <- c(.20, .20, .20, .40)
expected
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, χ²(3) = 41.60, p < .001.
#The difference was moderate, (Cohen's W = .41).

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