library(readxl)
A4Q1 <- read_excel("C:/Users/mercy/OneDrive - Saint Louis University/AA 5221/Assignment 4/A4Q1 (1).xlsx")

table(A4Q1$flavor)

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

observed <- table(A4Q1$flavor)
barplot(observed, 
        main = "flavor", 
        xlab = "flavor", 
        ylab = "Frequency", 
        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 distribution of ice cream sales from August last year and the expected frequencies.
#The results showed that there was a difference between the observed and expected frequencies, χ²(2) = 41.6, p <.
#The difference was moderate, (Cohen's W = 0.41).