If you must insist on treating these three points as independent - which I can see little justification for doing, but maybe that's just me - you do a (casualties, indictments, convictions) plot and run a linear fit against all three points in a given series at the same time. This way you get some more meaningful (implicit) assumptions about the way the uncertainties look.
- Jake If you only spend 20 minutes of the rest of your life on economics, go spend them here.
Or, rather, three fits.
One for all six rows in Vladimir's table - that's the "null hypothesis".
One for the 3 Serb rows and the 3 non-serb rows. That's more or less equivalent to was was done in the diary.
Or you could do a test on whether the 3 Serb and 3 non-Serb points fall above or below the "null hypothesis" regression line. The trouble is, with only 6 points you probably can't say anything with 95% confidence. Most economists teach a theoretical framework that has been shown to be fundamentally useless. -- James K. Galbraith
I would be opposed to fitting the slope as well as the intercept in your model, because we already only have three points for every fit parameter - and you fit a number of parameters comparable to your number of data points at the peril of talking nonsense...
This actually makes it look worse for Vladimir's hypothesis. The fit is this:
Coefficients: (Intercept) -6.095 Response: log(indicted) - log(casualties) Df Sum Sq Mean Sq F value Pr(>F) Residuals 5 1.24772 0.24954
