##### RUN LINES 4-25 TO GENERATE ONE SIMULATED DATA SET FOR EXERCISE 5 #####
##### (Based on Kery 2010) - Note that length has been standardized! #######

n.groups <- 20
n.sample <- 10
n <- n.groups*n.sample
pop <- gl(n=n.groups,k=n.sample)
orig.length <- runif(n,200,400)
mn <- mean(orig.length)
sd <- sd(orig.length)
length <- (orig.length-mn)/sd
Xmat <- model.matrix(~pop*length-1-length)
intercept.mean <- 1550
intercept.sd <- 100
slope.mean <- 200
slope.sd <- 50
intercept.effects <- rnorm(n=n.groups,mean=intercept.mean,sd=intercept.sd)
slope.effects <- rnorm(n=n.groups,mean=slope.mean,sd=slope.sd)
all.effects <- c(intercept.effects,slope.effects)
lin.pred <- Xmat[,]%*%all.effects
eps <- rnorm(n=n,mean=0,sd=5)
mass <- lin.pred+eps
elephants <- as.data.frame(cbind(mass,length,pop))
colnames(elephants) <- c("mass","length","pop")
elephants