Evaluation of the Performance of Jackson County Judges

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The objective of this analysis was to evaluate the performance of Jackson County judges. To achieve the goal of the investigation, a total of 182, 908 cases handled by 40 judges belonging to the Common Pleas Court, Domestic Relations Court and Municipal Court were analyzed. The study employs probability and conditional probability to rank each of the judges, as well as each court to determine which judges are doing a good job and the ones making too many mistakes. The probability of the appealed or reversed cases was determined using the formula below;

Likelihood of given type of a case = number of occurences of the case total number of cases disposed         (1) (Papoulis & Pillai, 2002)

The judges and courts with the lowest probability of reversed and appealed cases were considered to be doing a good job. 

The analysis also involved the study of probability of appealed cases to be reversed which was calculated using the following expressions;

P (R/A) = P (R ∩ A)P (A)                          (2) (Hogg & Craig, 1995)

P (R ∩ A) = P(R / A) P(A)       (3) (Evans et.al, 2003)


P (A) – Probability of appealed cases

P (R) – Probability of reserved cases


Following the overall rank, the performance of doctors from the best to the poorest performer at the court of Common pleas are as given below;

  1. Richard T. Andrias, David Friedman
  2. Karla Moskowitz
  3. Leland G. DeGrasse 
  4. David B. Saxe, John W. Sweeeny Jr. 
  5. Helen E. Freedman
  6. Peter Tom
  7. Dianne T. Renwick 
  8. Rosalyn H. Richter 
  9. Sallie Manzanet – Daniels 
  10. Angela M. Mazzarelli 
  11. Darcel D. Clark, Rolando T. Acosta 
  12. Paul G. Feinman 
  13. Judith J. Gische 

For the Domestic Relation courts, the list of the judges from the best to the poorest performer is as given below;

  1. Edward O. Spain 
  2. Leslie E. Stein 
  3. John A. Lahtinen
  4. William E. McCarthy 

For the Municipal courts, the list below gives the best to the poorest performing judge based on overall ranking;

  1. Dianne T. Renwick 
  2. Angela M. Mazzarelli
  3. Judith J. Gische 
  4. Luis A. Gonzalez 
  5. Peter Tom,  John C. Egan Jr
  6. Rolando T. Acosta
  7. Leland G. DeGrasse
  8. Darcel D. Clark 
  9. David Friedman
  10. David B. Saxe 
  11. Paul G. Feinman 
  12. Helen E. Freedman, Rosalyn H. Richter
  13. Sallie Manzanet – Daniels
  14. Elizabeth A. Garry
  15. Karla Moskowitz, Richard T. Andrias 
  16. Leslie E. Stein  
  17. John W. Sweeny Jr. 
  18. Rosalyn H. Richer 


Common pleas court  Domestic Relation court Municipal court 
Probability of case reversal  0.63021 0.01717 0.11677
Probability of case appeal  0.07261 0.00279 0.02565208

Domestic relation courts have the smallest probability of case reversal and also for cases appealed. Thus, the domestic relation court can be considered to be the most efficient followed by the municipal court while the court of common pleas is the last in terms of performance. 


The experiment was successful done. It was found that domestic relation court is the most performing court followed by the municipal court and then, the court of common pleas. Also, it was concluded that at the court of common pleas, domestic relation court and at the municipal court the following judges are the best performers; Richard T. Andrias, David Friedman (court of common pleas), Edward O. Spain (domestic relation court) and Dianne T. Renwick (municipal court). Lastly, the following judges can be taken as poor performers; Judith J. Gische (court of common pleas), Luis A. Gonzalez (domestic relation court) and Rosalyn H. Richer (municipal court)

Did you like this sample?
  1. Evans, J. S. B., Handley, S. J., & Over, D. E. (2003). Conditionals and conditional probability. Journal of Experimental Psychology: Learning, Memory, and Cognition29(2), 321.
  2. Hogg, R. V., & Craig, A. T. (1995). Introduction to mathematical statistics.(5″” edition) (pp. 269-278). Upper Saddle River, New Jersey: Prentice Hall.
  3. Papoulis, A., & Pillai, S. U. (2002). Probability, random variables, and stochastic processes. Tata McGraw-Hill Education.
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