Fenois = c(337.311, 344.874, 342.353, 325.546, 333.950, 330.588, 328.067, 328.067, 318.824, 331.429, 333.950, 334.790, 336.471, 338.151, 342.353, 259.160, 252.437, 268.403, 265.882, 266.723, 287.731,  88.571, 88.571,  90.252,  41.513,  52.437,  49.076,  88.571,  88.571,  90.252,  64.202,  60.000,  61.681)

Cor = factor(c(rep("ambar",6),rep("ambar_claro",3),rep("ambar",6),rep("ambar_claro",6),rep("branco",6),

                rep("extra_ambar_claro",3),rep("branco",3)))   

Fenois; Cor

boxplot(Fenois~Cor,ylab=expression(paste("Fenois","  ","(",mg," ",kg^-1,")")), xlab="cor",names=c("Âmbar", "Âmbar Claro", "Branco", "Extra Âmbar Claro"))

tapply(Fenois, Cor, mean)

tapply(Fenois, Cor, sd)

tapply(Fenois, Cor, var)

#Teste de homogeneidade de variâncias

bartlett.test(Fenois ~ Cor)

#Gráficos para avaliar a  variável resposta

qqnorm(Fenois)

qqline(Fenois)

hist(Fenois)

boxplot(Fenois)

#Transformação Box-Cox

require(MASS)

boxcox(Fenois~Cor, lambda = seq(-2, 2, 1/10))     

boxcox(Fenois~Cor, lambda = seq(0.5, 1.5, 1/100))

#Optando por lambda = 0.6

Fenois2 = ((Fenois^0.6) - 1)/0.6

par(mfrow=c(1,2))

boxplot(Fenois~Cor,ylab=expression(paste("Fenois","  ","(",mg," ",kg^-1,")")), xlab="cor",names=c("Âmbar", "Âmbar Claro", "Branco", "Extra Âmbar Claro"))

boxplot(Fenois2~Cor,ylab=expression(paste("Fenois","  ","(",mg," ",kg^-1,")")), xlab="cor",names=c("Âmbar", "Âmbar Claro", "Branco", "Extra Âmbar Claro"))

bartlett.test(Fenois2 ~ Cor)