library(readxl)
library(ggplot2)
library(rcompanion)
DatasetA2 <- read_excel("D:/SLU/AdvAppliedAnalytics/DatasetA2.xlsx")
table(DatasetA2$FavoriteDrink)
##
## Coffee Soda Tea Water
## 26 29 28 17
ggplot(DatasetA2, aes(x = FavoriteDrink, fill = FavoriteDrink)) +
geom_bar() +
labs(
x = "FavoriteDrink",
y = "Frequency",
title = "Distribution of Favorite Drink"
) +
theme(
text = element_text(size = 14),
axis.title = element_text(size = 14),
axis.text = element_text(size = 14),
plot.title = element_text(size = 14),
legend.position = "none"
)
observed <- c(26, 29, 28, 17)
expected <- c(0.25, 0.25, 0.25, 0.25)
chi_result <- chisq.test(observed, p = expected)
chi_result
##
## Chi-squared test for given probabilities
##
## data: observed
## X-squared = 3.6, df = 3, p-value = 0.308
The p-value is 0.308 which is greater than 0.05, so the result is not statistically significant.
A chi-square goodness-of-fit test indicated that the observed frequencies were not different from the expected frequencies, χ²(3) = 3.60, p = .308 which is greater than 0.05, so the result is not statistically significant.