A5Q1

library(readxl)
library(ggpubr)

## Loading required package: ggplot2

library(rmarkdown)
library(readxl)

A5Q1_1 <- read_excel("C:/Users/edavi/OneDrive/Desktop/A5Q1-1.xlsx")
View(A5Q1_1)

observed<-table(A5Q1_1$flavor)
View(A5Q1_1)

print(observed)

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

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)

print(chi_result)

## 
##  Chi-squared test for given probabilities
## 
## data:  observed
## X-squared = 41.6, df = 3, p-value = 4.878e-09

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))

print(w)

## [1] 0.4079216

[1] 0.4079216

A Chi-Square Goodness of Fit test was conducted to determine if there was a difference between the oberserved flavor frequencies and the expected frequencies. The results showed that there was a difference between the observed and expected frequencies, X-squared (3) = 41.6, p = < .001. The difference was moderate, (Cohen’s W = .41)