To put the issue of conviction rates to rest, consider the following table

	    Total Serb Croat Bosniac Albanian Unknown Macedonian
Indicted      157  101	  32	   9	    9	    4	       2
Convicted      69   48	  13	   4	    3	    0	       1
Dismissed      18   11	   2	   0	    1	    4	       0
Ongoing        16    9	   6	   1	    0	    0	       0
Acquitted      14    2	   4	   3	    4	    0	       1
Died	       14   12	   1	   1	    0	    0	       0
Unknown        13    9	   4	   0	    0	    0	       0
Transferred    11    8	   2	   0	    1	    0	       0
At Large	2    2	   0	   0	    0	    0	       0

under the hypothesis that the court is not biased, this is the expected distribution (obtained by taking the "total" column and the "indicted" row and multiplying them)

	    Total   Serb  Croat Bosniac Albanian Unknown Macedonian
Indicted      157 101.00 32.000   9.000    9.000   4.000     2.0000
Convicted      69  44.40 14.100   3.960    3.960   1.760     0.8790
Dismissed      18  11.60  3.670   1.030    1.030   0.459     0.2290
Ongoing        16  10.30  3.260   0.917    0.917   0.408     0.2040
Acquitted      14   9.01  2.850   0.803    0.803   0.357     0.1780
Died	       14   9.01  2.850   0.803    0.803   0.357     0.1780
Unknown        13   8.36  2.650   0.745    0.745   0.331     0.1660
Transferred    11   7.08  2.240   0.631    0.631   0.280     0.1400
At Large	2   1.29  0.408   0.115    0.115   0.051     0.0255

At this point one would have to aggregate some of the rows and columns on order to ensure that the "expected" number in each cell is at least about 5. But we won't do this yet. First, for each cell in the table (except for the "Total" column and the "indicted" row) we compute (observer - expected)^2/(expected) as a measure of the deviation from the null hypothesis. We get

	    Total Serb Croat Bosniac Albanian Unknown Macedonian
Total	     73.4  7.5	 5.9	 8.6	 15.8	 30.9	     4.7
Convicted     2.4  0.3	 0.1	 0.0	  0.2	  1.8	     0.0
Dismissed    29.4  0.0	 0.8	 1.0	  0.0	 27.3	     0.2
Ongoing       4.0  0.2	 2.3	 0.0	  0.9	  0.4	     0.2
Acquitted    28.8  5.5	 0.5	 6.0	 12.7	  0.4	     3.8
Died	      3.6  1.0	 1.2	 0.0	  0.8	  0.4	     0.2
Unknown       2.7  0.0	 0.7	 0.7	  0.7	  0.3	     0.2
Transferred   1.4  0.1	 0.0	 0.6	  0.2	  0.3	     0.1
At Large      1.1  0.4	 0.4	 0.1	  0.1	  0.1	     0.0

Where we have added the numbers by row and by column into the "Total" row and column. The total deviation is 73.4 which should be compared with a chi-square variable with 47 degress of freedom (for 6 ethinicities x 8 trial status - 1). The p-value is 0.00819 so appears to be a significant deviation. The trouble is that the single largest deviation comes from the 4 "dismissed" cases of "unknown" ethnicity, and also from the fact that there are a lot of cells with expected numbers of observations below 1 which makes the approximation (observed - expected)^2/expected a very bad approximation to the true likelihood function, which is what we're estimating here.

So, what we need to do is to aggregate the "unknown" (I choose to do this with the smallest category, "Macedonian" into "other") and also the "al large" - which I will aggregate with the "Ongoing".

Most economists teach a theoretical framework that has been shown to be fundamentally useless. -- James K. Galbraith