library(readxl)
library(ggpubr)
## Loading required package: ggplot2
A5Q1 <- read_excel("downloads/A5Q1-1.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)))

Flavor= Chocolate: 20%, Strawberry: 20%, Mango: 20%, Vanilla: 40%

expected <- c(.20, .20, .20, .40)

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-Squared Goodness of Fit 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, x²(3) = 41.6, p < .001.

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