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...