multivariate sorting / ranking I have data for 1000 students' performance over 10 different tests on a scale of 0 -100 (a 1000 rows X 10 col matrix).
I calculated the mean score and the associated coefficient of variation for each student.
Now I wish to sort / rank students who consistently perform better, that is, have a high mean score and low coeff. of variation.
Can anyone suggest a ranking scheme based on two objective variables (mean score and coeff. of variation).
Thanks.
 A: There are numerous ways to do this.  I would translate the score into a standard normal calculation. So you could think of it as the probability that each student could score higher than X*.  To a certain degree X is arbitrary, but I would set X to the mean of all test scores.  Since you don't have listed specific data or a specific language I'm going to just write out the steps you would need to preform in any programming language.
   Step 1) Calculate X = mean of all tests scores
   Step 2) Calculate z = (each student's average - X)/(std dev for each student)
   Step 3) Calculate cumulative normal distribution(z)

*This would be the probability that a student scores higher than the average student on a test assuming that test scores are normally distributed.  The validity of that assumption is up for some debate, but if you are simply trying to rank them in order, this would give you the correct order.  If you are trying to say student X is z% better than student Y then the assumption of the underlying distribution matters. 
