#Rolling down the river

set.seed(4243)
yield1 <- matrix(scan(),10,10,byrow=T)
6 17 20 38 47 55 69 76 82 97
7 14 23 34 43 56 63 75 81 92
2 14 28 30 50 50 62 80 85 96
9 15 27 34 43 51 65 72 88 91
4 15 28 32 44 50 64 76 82 97
5 16 27 31 48 59 69 72 86 99
5 18 28 34 50 60 62 75 90 90
8 15 20 38 40 54 62 77 88 93
7 17 29 39 44 53 61 77 80 90
7 19 22 33 49 53 67 76 86 97

yield1

example.mean <- NULL
example.sum  <- NULL
example.mean.horizontal <- NULL
example.sum.horizontal <- NULL
example.mean.vertical <- NULL
example.sum.vertical <- NULL

j=1
for (j in 1:100){
#simple random sample
a <- round(runif(10)*100)
a

#vertical stratified sample
b <- round(runif(10)*10)
b

#hortizontal stratified sample
c<- round(runif(10)*10)
c

#simple random sample
selection.table <- as.vector(t(yield1))
example.mean <- c(example.mean,mean(selection.table[a]))
example.sum <- c(example.sum,sum(selection.table[a]))

#vertical strata
selection.vertical <- NULL
for (i in 1:10){
selection.vertical <- c(selection.vertical,yield1[b[i],i])
}

example.mean.vertical <- c(example.mean.vertical,mean(selection.vertical))
example.sum.vertical <- c(example.sum.vertical,sum(selection.vertical))

#horizontal strata
selection.horizontal <- NULL
for (i in 1:10){
selection.horizontal <- c(selection.horizontal,yield1[i,c[i]])
}

example.mean.horizontal <- c(example.mean.horizontal,mean(selection.horizontal))
example.sum.horizontal <- c(example.sum.horizontal,sum(selection.horizontal))
}

#merge for means
compare.means <- as.data.frame(rbind(cbind(example.mean,rep(1,100)), cbind(example.mean.horizontal,rep(2,100)), cbind(example.mean.vertical,rep(3,100))))
names(compare.means) <- c("means","sampling")

boxplot(means~sampling,data=compare.means, main="Comparison of Sampling Strategies",xlab="Sampling Strategy (1:SRS, 2:horizontal, 3:vertical)", ylab="Mean Yield")

boxplot(means~sampling,data=compare.means, main="Comparison of Sampling Strategies",xlab="Sampling Strategy (1:SRS, 2:horizontal, 3:vertical)", ylab="Mean Yield",notch=TRUE)

library(vioplot)
x1 <- compare.means$means[compare.means$sampling==1]
x2 <- compare.means$means[compare.means$sampling==2]
x3 <- compare.means$means[compare.means$sampling==3]
vioplot(x1, x2, x3, names=c("Simple Random Sampling", "Horizontal Strat", "Vertical Strat"),col="gold")
title("Violin Plots of Mean Yield")


#farmer choice
#> mean(yield1[,1])
#[1] 6
#> sum(yield1[,1])
#[1] 60