library(ggplot2)
ggplot(sanguineo, aes(x = CONCENTRACION, y = VOLUMEN)) +
geom_boxplot(fill = "grey80", colour = "blue") +
scale_x_discrete() + xlab("Concentraciones") +
ylab("Volumen sangu?neo")
``{r anova} anova.sanguineo = aov(VOLUMEN ~ CONCENTRACION+GRUPO, data=sanguineo) summary(anova.sanguineo)
```r
anova.sanguineo = aov(VOLUMEN ~ CONCENTRACION+GRUPO, data=sanguineo)
summary(anova.sanguineo)
## Df Sum Sq Mean Sq F value Pr(>F)
## CONCENTRACION 3 12.550 4.183 6.016 0.00964 **
## GRUPO 4 3.755 0.939 1.350 0.30797
## Residuals 12 8.345 0.695
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Con base en la tabla se observa diferencias significativas en el efecto asociada al.
Interpretacion pruebas normalidad
e<-anova.sanguineo$residuals ##### residuales
shapiro.test(e) #### Normalidad
##
## Shapiro-Wilk normality test
##
## data: e
## W = 0.95529, p-value = 0.4545
hist(e, freq=FALSE)
curve(dnorm(x,mean(e), sd(e)), xlim=c(-1.5,1.5), add=TRUE, col=2)
library(carData)
library(car)
#####HOMOGENEIDAD
leveneTest(e ~ as.factor(CONCENTRACION), data = sanguineo, center = "median") #####homogeneidad
library(agricolae) #### PAQUETE DE PRUEBAS POST-ANOVA
##### PRUEBA TUKEY
HSD.test(anova.sanguineo,"CONCENTRACION",
alpha=0.05, console=TRUE, group=FALSE)
##
## Study: anova.sanguineo ~ "CONCENTRACION"
##
## HSD Test for VOLUMEN
##
## Mean Square Error: 0.6954167
##
## CONCENTRACION, means
##
## VOLUMEN std r Min Max
## T1 5.0 1.1575837 5 4.1 6.5
## T2 6.4 0.6403124 5 5.3 6.9
## T3 4.2 0.2000000 5 4.0 4.5
## T4 5.4 1.1113055 5 4.2 6.9
##
## Alpha: 0.05 ; DF Error: 12
## Critical Value of Studentized Range: 4.19866
##
## Comparison between treatments means
##
## difference pvalue signif. LCL UCL
## T1 - T2 -1.4 0.0855 . -2.9658432 0.1658432
## T1 - T3 0.8 0.4581 -0.7658432 2.3658432
## T1 - T4 -0.4 0.8714 -1.9658432 1.1658432
## T2 - T3 2.2 0.0061 ** 0.6341568 3.7658432
## T2 - T4 1.0 0.2800 -0.5658432 2.5658432
## T3 - T4 -1.2 0.1586 -2.7658432 0.3658432