ruta_Ensamble <-"C:/Users/lenovo/Downloads/Grado_alcohólico.xlsx"
excel_sheets(ruta_Ensamble)
[1] "VINOS POR PRUEBA FQ."
casoDBCA1 <- read_excel(ruta_Ensamble)
print(casoDBCA1)
VOL<-factor(casoDBCA1$`Grado_alcohólico_volumétrico_%Volumen`)
VAR<-factor(casoDBCA1$Variedad)
VOL1<-as.numeric(VOL)
par(mfrow=c(1,1))
boxplot(split(VOL,VAR),xlab="Grado_alcohólico_volumétrico_%Volumen", ylab="Variedad")

resaov<-aov(VOL1 ~ VAR)
anova(resaov)
Analysis of Variance Table
Response: VOL1
Df Sum Sq Mean Sq F value Pr(>F)
VAR 6 339.71 56.619 0.7115 0.6438
Residuals 24 1909.96 79.582
cv.model(resaov)
[1] 57.37486
euc.lm <- lm(VOL1 ~ VAR)
anova(euc.lm , test="F")
Analysis of Variance Table
Response: VOL1
Df Sum Sq Mean Sq F value Pr(>F)
VAR 6 339.71 56.619 0.7115 0.6438
Residuals 24 1909.96 79.582
shapiro.test(euc.lm$res)
Shapiro-Wilk normality test
data: euc.lm$res
W = 0.96325, p-value = 0.3548
plot(anova(euc.lm , test="F"))
Error: objeto 'euc.lm' no encontrado
fitb <- fitted(resaov)
Error: objeto 'resaov' no encontrado
res_stb <- rstandard(resaov)
Error: objeto 'resaov' no encontrado
plot(fitb,res_stb,xlab="Grado_alcohólico_volumétrico_%Volumen", ylab="Variedad",abline(h=0))
Error: objeto 'fitb' no encontrado
leveneTest(GRADO1 ~ VAR, center = "median")
Error en eval(predvars, data, env): objeto 'GRADO1' no encontrado
summary(sk)
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