## first "attach" the data, allowing you to refer
## directly to the variable names.
attach(meadow)

## this sets up the axes and labels for the plot without
## plotting the data (this is why type="n").
plot(intensity,flowers,type="n",xlab="Intensity",ylab="Flowers")

## add points to the plot, coded "0" for the "Late" group
points(intensity[time==0],flowers[time==0],pch="0")

## add points to the plot, coded "1" for the "Early" group
points(intensity[time==1],flowers[time==1],pch="1")

## add a title
title("Flowers vs. Intensity, Equal Lines Model")

## fit the regression model.  "equal lines model"
## is now an Splus object, containing information
## on the intercept (coefficients[1]) and slope (coefficients[2])
equal.lines.model <- lm(flowers~intensity)

## name the intercept and slope
beta0 <- equal.lines.model$coefficients[1]
beta.intensity <- equal.lines.model$coefficients[2]

## add a line to the plot with given intercept and slope
abline(beta0,beta.intensity)