library(readxl)
library(ggplot2)
A5Q1 <- read_excel("A5Q1.xlsx")
observed <- table(A5Q1$flavor)
observed
##
## Chocolate Mango Strawberry Vanilla
## 87 32 57 74
ggplot(A5Q1, aes(x = flavor, fill = flavor)) +
geom_bar()
expected <- c(0.2, 0.2, 0.2, 0.4)
chi_result <- chisq.test(x = observed, p = expected)
chi_result
##
## Chi-squared test for given probabilities
##
## data: observed
## X-squared = 41.6, df = 3, p-value = 4.878e-09
w <- sqrt(as.numeric(chi_result$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) = 41.6, p < .001.
# The difference was moderate, (Cohen's W = .41).