A<-c(264,260,258,241,262,255)
B<-c(208,220,216,200,213,206)
C<-c(220,213,219,225,230,228)
D<-c(217,226,215,227,220,222)
df<-data.frame(A=A,B=B,C=C,D=D)
df
## A B C D
## 1 264 208 220 217
## 2 260 220 213 226
## 3 258 216 219 215
## 4 241 200 225 227
## 5 262 213 230 220
## 6 255 206 228 222
N=24
n=6
k=4
SCT=sum(df*df)-sum(df)**2/N
SCT
## [1] 8150.958
st=sapply(df,sum)
n<-sapply(df,length)
SCTrat=sum(st*st/n)-sum(df)**2/N
SCTrat
## [1] 7227.792
SCE=SCT-SCTrat
SCE
## [1] 923.1667
CMTrat=SCTrat/(k-1)
CMTrat
## [1] 2409.264
CME=SCE/(N-k)
CME
## [1] 46.15833
Fo=CMTrat/CME
Fo
## [1] 52.19564
qf(0.95,k-1,N-k)
## [1] 3.098391
1-pf(Fo,k-1,N-k)
## [1] 1.217115e-09
df<-stack(df)
df
## values ind
## 1 264 A
## 2 260 A
## 3 258 A
## 4 241 A
## 5 262 A
## 6 255 A
## 7 208 B
## 8 220 B
## 9 216 B
## 10 200 B
## 11 213 B
## 12 206 B
## 13 220 C
## 14 213 C
## 15 219 C
## 16 225 C
## 17 230 C
## 18 228 C
## 19 217 D
## 20 226 D
## 21 215 D
## 22 227 D
## 23 220 D
## 24 222 D
names(df)=c("Y","Trat")
str(df)
## 'data.frame': 24 obs. of 2 variables:
## $ Y : num 264 260 258 241 262 255 208 220 216 200 ...
## $ Trat: Factor w/ 4 levels "A","B","C","D": 1 1 1 1 1 1 2 2 2 2 ...
modelo<-aov(Y~Trat,data=df)
summary(modelo)
## Df Sum Sq Mean Sq F value Pr(>F)
## Trat 3 7228 2409.3 52.2 1.22e-09 ***
## Residuals 20 923 46.2
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1