library(readxl)
A4Q1 <- read_excel("//apporto.com/dfs/SLU/Users/sararaewomack_slu/Desktop/Assignment 4/A4Q1.xlsx")
observed <- table(A4Q1$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)
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(3) = 41.60, p < .001
# The difference was  moderate (Cohen's W = .41).