R commands for the two-factor factorial

#Partial dataset:

 y <- c(130, 155,  74, 180,  20,  70,  82,  58, 150, 188, 159, 126,  25,  70,  58,  45)
 type <- as.factor(rep(1:2,each=8))
 temp <- as.factor(rep(1:2, each=4, times=2))
 data <- data.frame(y,type,temp)
 data

 means <- matrix(nrow=2,ncol=2)
 for(i in 1:2) {for (j in 1:2) means[i,j] <- mean(y[type==i & temp == j])}

 means

 par(mfrow=c(1,2))
 interaction.plot(type,temp,y)
 interaction.plot(temp,type,y)


# Full dataset:

 y <- c(130, 155,  74, 180,  34,  40,  80,  75,  20,  70,  82,  58, 150, 
   188, 159, 126, 136, 122, 106, 115,  25,  70,  58,  45, 138, 110, 168,
   160, 174, 120, 150, 139,  96, 104,  82,  60)

 type <- as.factor(rep(1:3,each=12))
 temp <- as.factor(rep(c(15,70,125),each=4,times=3))
 data <- data.frame(type, temp, y)
 data


 par(mfrow=c(1,2))
 interaction.plot(type,temp,y)
 interaction.plot(temp,type,y)


 means <- matrix(nrow=3,ncol=3)
 for(i in 1:3) {for (j in 1:3) means[i,j] <- mean(y[type==i & temp == c(15,70,125)[j]])}
 means
 g <- lm(y~type+temp+type*temp)
 anova(g)