set.seed(123)

# Simulating hair and eye color data
hair_color <- sample(c("Black", "Blonde", "Brown"), size = 100, replace = TRUE)
eye_color <- sample(c("Blue", "Brown", "Green"), size = 100, replace = TRUE)
df <- data.frame(hair_color, eye_color)

# Conducting Chi-Squared test to check for an association between hair color and eye color
# H0: There is no association between hair color and eye color
# H1: There is an association between hair color and eye color
result <- chisq.test(df$hair_color, df$eye_color)

# Print the result of the test
print(result)

# If the p-value is less than the significance level (commonly 0.05), we reject the null hypothesis.
# This means we have evidence to suggest there is an association between hair color and eye color.
# If the p-value is greater than the significance level, we fail to reject the null hypothesis.
# This means we do not have sufficient evidence to suggest there is an association between hair color and eye color.