library('arm')
acorn=read.table('acorn1.txt',header=T)
acorn
str(acorn)

#1
attach(acorn)
sapply(split(Acorn_size,Region),mean)
sapply(split(Acorn_size,Region),sd)

#2
xyplot(Acorn_size~Range)
xyplot(Acorn_size~Range, groups=Region)
xyplot(Acorn_size~Range, groups=Region, pch=c(1,3), key=list(space='top', columes=2, text=list(levels(Region)), points=list(col=trellis.par.get('superpose.symbol')$col[1:2], pch=c(1,3)) ) )
xyplot(Acorn_size~Range, groups=Region, type=c('p','r'))

#3
detach(acorn)
lm1=lm(Acorn_size~Range, data=acorn[1:28,])
lm1=lm(Acorn_size~Range, data=acorn[Region=='Atlantic',])
display(lm1)
display(lm1,digit=5)

xyplot(log(Acorn_size)~Range, data=acorn[1:28,], type=c('p','r'))
lm2=lm(log(Acorn_size)~Range, data=acorn[1:28,])
display(lm2,digit=5)

xyplot(log(Acorn_size)~log(Range), data=acorn[1:28,], type=c('p','r'))
lm3=lm(log(Acorn_size)~log(Range), data=acorn[1:28,])
display(lm3)

#4
lm4=lm(log(Acorn_size)~log(Range), data=acorn)
lm5=lm(log(Acorn_size)~log(Range)+Region, data=acorn)
lm6=lm(log(Acorn_size)~log(Range)*Region, data=acorn)

display(lm4)
display(lm5)
display(lm6)

xyplot(log(Acorn_size)~log(Range), data=acorn, type=c('p','r'))
xyplot(log(Acorn_size)~log(Range), data=acorn, groups=Region, type=c('p','r'))

#5
xyplot(log(Acorn_size)~log(Range), data=acorn[-39,], groups=Region, type=c('p','r'))
lm7=lm(log(Acorn_size)~log(Range)*Region, data=acorn[-39,])
display(lm7)

#6
exp( lm7$coef[1] + lm7$coef[2] * log(1000) + lm7$coef[3] * 1 + lm7$coef[4] * log(1000))
exp(predict(lm7,data.frame(Region='California',Range=1000)))
xyplot(Acorn_size~Range, data=acorn[29:39,])