I want to conduct an experiment to find out whether the CO2-production of soil changes with high amounts of rainfall. Therefore, I want to group 8 soil samples into two different groups. One group is control, one group is treatment. Due to time, space and money restrictions, I can only have four replicates for each group.
I have some pre-experiment CO2-production rates of these 8 samples that I would like to use to group the subjects. The two groups should be as similar as possible before the treatment starts (equal mean and variance).
How can I programmatically determine the "best" division into groups?
Data of pre-test CO2 production are below.
Any direct help or linkage to other websites/posts is greatly appreciated. Please let me know if and how I can improve the question. Some google-fu was to no avail.
#### Data: y1-y8 are the soil samples, the values are CO2 procution rates
y1 <- 10
y2 <- 20
y3 <- 22
y4 <- 30
y5 <- 15
y6 <- 12
y7 <- 28
y8 <- 26
group1.1 <- c(y1,y2,y3,y4)
group1.2 <- c(y5,y6,y7,y8)
group2.1 <- c(y4,y7,y8,y3)
group2.2 <- c(y1,y2,y5,y6)
boxplot(group1.1, group1.2,las=1) # not too bad, but I am sure it can be done better...but how?
boxplot(group2.1, group2.2,las=1) # bad...