GRADO DE ALCOHOL

file.choose()

[1] "C:\\Users\\Usuario\\Downloads\\Grado_alcohólico.xlsx"

ruta_Ensamble <-"C:\\Users\\Usuario\\Downloads\\Grado_alcohólico.xlsx"

excel_sheets(ruta_Ensamble )

[1] "VINOS POR PRUEBA FQ."

casoDBCA1<-read_excel(ruta_Ensamble)

print(casoDBCA1)

#secrea un objeto tipo factor

VARD<-factor(casoDBCA1$Variedad)

GRADVOL<- as.vector(casoDBCA1$`Grado_alcohólico_volumétrico_%Volumen`)

#Luego el vector TIEM se convierte a un vector ALT1 de tipo numérico

GRADVOL1<-as.numeric(GRADVOL)

#Diagrama de cajas de dispersión (Box plot)

par(mfrow=c(1,1))

boxplot(split(GRADVOL1,VARD),xlab="Variedad", ylab="`Grado_alcohólico_volumétrico_%Volumen`")

resaov<-aov(GRADVOL1 ~ VARD)

anova(resaov)

Analysis of Variance Table

Response: GRADVOL1
          Df  Sum Sq Mean Sq F value Pr(>F)
VARD       6  3.3901 0.56502  0.7298 0.6302
Residuals 24 18.5813 0.77422               

3.- Análisis de varianza usando la función modelo lineal (lm) Linear model #Coeficiente de variación

cv.model(resaov)

[1] 6.887564

euc.lm <- lm(GRADVOL1 ~ VARD )

anova(euc.lm , test="F")

Analysis of Variance Table

Response: GRADVOL1
          Df  Sum Sq Mean Sq F value Pr(>F)
VARD       6  3.3901 0.56502  0.7298 0.6302
Residuals 24 18.5813 0.77422               

4.- Evaluación de los Supuestos del modelo estadístico matemático #Prueba de normalidad Shapiro-Wilk

shapiro.test(euc.lm$res)

    Shapiro-Wilk normality test

data:  euc.lm$res
W = 0.94655, p-value = 0.1253

fitb <- fitted(resaov)

res_stb <- rstandard(resaov)

plot(fitb,res_stb,xlab="Valores predichos", ylab="Residuos estandarizados",abline(h=0))

6.- Pruebas de comparación múltiple de medias #Método de la diferencia mínima significativa, Least Significant Difference (LSD)

outLSD <-LSD.test(resaov, "VARD",console=TRUE)

Study: resaov ~ "VARD"

LSD t Test for GRADVOL1 

Mean Square Error:  0.7742194 

VARD,  means and individual ( 95 %) CI

Alpha: 0.05 ; DF Error: 24
Critical Value of t: 2.063899 

Groups according to probability of means differences and alpha level( 0.05 )

Treatments with the same letter are not significantly different.

outHSD<-HSD.test(resaov, "VARD",console=TRUE)

Study: resaov ~ "VARD"

HSD Test for GRADVOL1 

Mean Square Error:  0.7742194 

VARD,  means

Alpha: 0.05 ; DF Error: 24 
Critical Value of Studentized Range: 4.541314 

Groups according to probability of means differences and alpha level( 0.05 )

Treatments with the same letter are not significantly different.

SNK.test(resaov, "VARD",console=TRUE)

Study: resaov ~ "VARD"

Student Newman Keuls Test
for GRADVOL1 

Mean Square Error:  0.7742194 

VARD,  means

Groups according to probability of means differences and alpha level( 0.05 )

Means with the same letter are not significantly different.

scheffe.test(resaov, "VARD",console=TRUE)

Study: resaov ~ "VARD"

Scheffe Test for GRADVOL1 

Mean Square Error  : 0.7742194 

VARD,  means

Alpha: 0.05 ; DF Error: 24 
Critical Value of F: 2.508189 

Groups according to probability of means differences and alpha level( 0.05 )

Means with the same letter are not significantly different.

duncan.test(resaov, "VARD",console=TRUE)

Study: resaov ~ "VARD"

Duncan's new multiple range test
for GRADVOL1 

Mean Square Error:  0.7742194 

VARD,  means

Groups according to probability of means differences and alpha level( 0.05 )

Means with the same letter are not significantly different.

LSD.test(resaov, "VARD", p.adj= "bon",console=TRUE)

Study: resaov ~ "VARD"

LSD t Test for GRADVOL1 
P value adjustment method: bonferroni 

Mean Square Error:  0.7742194 

VARD,  means and individual ( 95 %) CI

Alpha: 0.05 ; DF Error: 24
Critical Value of t: 3.395988 

Groups according to probability of means differences and alpha level( 0.05 )

Treatments with the same letter are not significantly different.