Y=c(14.823,
14.676,
14.720,
14.5141,
15.065,
25.151,
25.401,
25.131,
25.031,
25.267,
32.605,
32.460,
32.256,
32.669,
32.111)
trat=rep(c("trat1","trat2","trat3"),each=5)
df<-data.frame(trat=trat,Y=Y)
modelo<-aov(Y~trat,data=df)
summary(modelo)
## Df Sum Sq Mean Sq F value Pr(>F)
## trat 2 788.3 394.2 10132 <2e-16 ***
## Residuals 12 0.5 0.0
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
boxplot(Y~trat,data=df)

h<-TukeyHSD(modelo)
h
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = Y ~ trat, data = df)
##
## $trat
## diff lwr upr p adj
## trat2-trat1 10.43658 10.10377 10.76939 0
## trat3-trat1 17.66058 17.32777 17.99339 0
## trat3-trat2 7.22400 6.89119 7.55681 0
plot(h)

res<-modelo$residuals
qqnorm(res)
qqline(res)

shapiro.test(res)
##
## Shapiro-Wilk normality test
##
## data: res
## W = 0.97219, p-value = 0.8891