library(readxl)
library(ggplot2)
A4Q1 <- read_excel("C:/Users/USER/OneDrive - Saint Louis University/AA 5221/Assignment 4/A4Q1.xlsx")
View(A4Q1)

observed <- table(A4Q1$flavor)
observed

## 
##  Chocolate      Mango Strawberry    Vanilla 
##         87         32         57         74

#Plot
barplot(observed,
        main = "flavor",
        xlab = "flavor",
        ylab = "Count",
        col = rainbow(length(observed)))

#Expected proportions
expected <- c(.20, .20, .20, .40)

#Chi-Square Goodness of fit test
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

#Calculate Cohen's W
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 frequencies and the expected frequencies. 
#The results showed that there was a difference between the observed and expected frequencies, X-squared = 41.6, df=3, p-value= 4.878e-09. 
#The difference was moderate. (Cohen's W= .41).