##### RUN LINES 4-20 TO GENERATE ONE SIMULATED DATA SET FOR EXERCISE 1 #####
##### (Based on Kery 2010) #################################################

n.groups <- 3
n.sample <- 10
n <- n.groups*n.sample 
x <- rep(1:n.groups, rep(n.sample,n.groups))
pop <- factor(x, labels = c("Orlando", "Tampa", "Miami"))
length <- runif(n,45,70)
Xmat <- model.matrix(~pop*length)
beta.vec <- c(-250,150,200, 6, -3, -4)
lin.pred <- Xmat[,]%*%beta.vec
eps <- rnorm(n,0,10)
mass <- lin.pred+eps
length.d <- c(length[1:10],length[11:20],length[21:30])
mass.d <- c(mass[1:10],mass[11:20],mass[21:30])
location <- c(rep(unique(pop)[1],10),rep(unique(pop)[2],10),rep(unique(pop)[3],10))
YOUR_DATA <- as.data.frame(cbind(location,length.d,mass.d))
YOUR_DATA$location <- factor(YOUR_DATA$location, labels = c("Orlando", "Tampa", "Miami"))
YOUR_DATA