# Set a seed for reproducibility of results
set.seed(123)

# Simulate the heights of plants grown under low, medium, and high light conditions
low_light <- rnorm(30, mean = 15, sd = 2) # 30 plants under low light
medium_light <- rnorm(30, mean = 20, sd = 3) # 30 plants under medium light
high_light <- rnorm(30, mean = 25, sd = 4) # 30 plants under high light

# Create a dataframe combining the heights and corresponding light conditions
df <- data.frame(
  height = c(low_light, medium_light, high_light),
  light = factor(rep(c("Low", "Medium", "High"), each = 30)) # light conditions
)

# Null Hypothesis (H0): The mean heights of plants grown under low, medium, and high light conditions are equal.
# Alternative Hypothesis (H1): At least one group's mean height is different from the others.

# Perform an Analysis of Variance (ANOVA) test to check if light conditions affect plant height
result <- aov(height ~ light, data = df) # height is the dependent variable, light is the independent variable

# Print the results of the ANOVA test, which include the F-statistic and the p-value
# If p-value < 0.05, we reject the null hypothesis and conclude that there's a significant difference in mean heights.
# If p-value > 0.05, we fail to reject the null hypothesis and conclude that there's not enough evidence of a significant difference.
summary(result)