library(readxl) library(ggplot2) library(gridExtra) library(phia) library(car) library(lsr) library(agricolae)
setwd(“C:/Users/anama/OneDrive/Desktop/Proyecto II/R/”) MRANOVA <- read_excel(“CMI_AF.xlsx”, col_types = c(“text”, “text”, “numeric”, “numeric”)) View(MRANOVA) names(MRANOVA) str(MRANOVA)
FactorA <- factor(MRANOVA\(Bacteria) FactorB <- factor(MRANOVA\)Medio) Respuesta_CMI <- MRANOVA$CMI
p1 <- ggplot(data = MRANOVA, aes(x = Medio, y = CMI)) + geom_boxplot() + theme_bw() p2 <- ggplot(data = MRANOVA, aes(x = Bacteria, y = CMI)) + geom_boxplot() + theme_bw() p3 <- ggplot(data = MRANOVA, aes(x = Medio, y = CMI, colour = Bacteria)) + geom_boxplot() + theme_bw() p4 <- ggplot(data = MRANOVA, aes(x = Bacteria, y = CMI, colour = Medio)) + geom_boxplot() + theme_bw()
grid.arrange(p1, p2, ncol = 2) p4
Modelo <- lm(CMI ~ FactorA * FactorB, data = MRANOVA) ANOVA <- aov(Modelo) summary(ANOVA)
Grafica <- interactionMeans(Modelo) plot(Grafica)
shapiro.test(rstandard(Modelo)) # Normalidad ncvTest(Modelo) # Homocedasticidad
par(mfrow = c(1,2)) plot(Modelo, which = 1:4) par(mfrow = c(1,1))
etaSquared(ANOVA)
outHSD_A <- HSD.test(ANOVA, “FactorA”, console = TRUE) outHSD_B <- HSD.test(ANOVA, “FactorB”, console = TRUE)