# Diseno 1: Factorial simple en arreglo completamente al azar
options(digits = 4)
set.seed(2024)

NDVI <- sort(
  runif(n = 36, min = 0.50, max = 0.75),
  decreasing = TRUE
)
NDVI

# SE: sin estres, S20: reduccion 20%, S40: reduccion 40%
estres <- gl(3, 12, 36, c("SE", "S20", "S40"))

d1 <- data.frame(NDVI, estres)

# Analisis descriptivo
boxplot(
  d1$NDVI ~ d1$estres,
  col = c("darkgreen", "green2", "orange")
)
abline(h = mean(NDVI), lwd = 2)

library(dplyr)
res1 <- d1 %>%
  group_by(estres) %>%
  summarise(
    media = mean(NDVI),
    mediana = median(NDVI),
    minimo = min(NDVI),
    maximo = max(NDVI),
    Q1 = quantile(NDVI, probs = 0.25),
    Q2 = quantile(NDVI, probs = 0.50),
    Q3 = quantile(NDVI, probs = 0.75),
    Varianza = var(NDVI),
    std = sd(NDVI),
    CV = 100 * sd(NDVI) / mean(NDVI)
  )

# Visualizacion tabular
# install.packages("DT")
library(DT)
datatable(res1)

# Analisis inferencial (ANOVA)
# H0: mu_SE = mu_S20 = mu_S40
# Ha: al menos una media difiere
anova1 <- aov(d1$NDVI ~ d1$estres)
summary(anova1)