############################################################################

### load data
data(ToothGrowth)

### turn dose into a factor
ToothGrowth$dose <- factor(ToothGrowth$dose)

### boxplot
boxplot(len ~ dose*supp, data=ToothGrowth, col="lightgray",
        xlab="Condition", ylab="Length of Odontoblasts", boxwex=0.5)

### two-way ANOVA
res <- aov(len ~ dose*supp, data=ToothGrowth)
summary(res)

### pairwise comparisons
TukeyHSD(res)

############################################################################

### load data
data(iris)

### correlation matrix
round(cor(iris[,1:4]), 2)

### scatterplot matrix
color <- c(rep("red", 50), rep("green", 50), rep("blue", 50))
pairs(iris[,1:4], pch=19, col=color, cex=.8)

############################################################################

### load data
data(Puromycin)

### plot data
plot(Puromycin$conc, Puromycin$rate, pch=19, ylim=c(50,220),
     col = ifelse(Puromycin$state == "treated", "red", "blue"),
     xlab = "Substrate Concentration (ppm)",
     ylab = "Reaction Velocity (counts/min/min)")

### add legend
legend("bottomright", inset=.02, pch=19, col=c("red","blue"), legend=c("treated","untreated"))

### fit regression model
res <- lm(rate ~ I(log(conc))*state, data=Puromycin)

### add fitted lines to plot
newdat <- data.frame(state="untreated", conc=seq(0, 1.5, .01))
lines(newdat$conc, predict(res, newdat), lwd=2, col="blue")
newdat <- data.frame(state="treated", conc=seq(0, 1.5, .01))
lines(newdat$conc, predict(res, newdat), lwd=2, col="red")

############################################################################