library(readxl)
library(ggpubr)
## Loading required package: ggplot2
A5Q1 <- read_excel("A5Q1.xlsx")
observed <- table(A5Q1$flavor)
observed
## 
##  Chocolate      Mango Strawberry    Vanilla 
##         87         32         57         74
barplot(observed,
        main = "flavor",
        xlab = "flavor",
        ylab = "Count",
        col = rainbow(length(observed)))

expected <- c(20, 20, 20, 40)
expected <- expected / sum(expected)
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 [flavor] frequencies and the expected frequencies.

The results showed that there [was] a difference between the observed and expected frequencies, χ²(2) = 41.60, p < .001.

The difference was moderate, (Cohen’s W = .41).