First, we will discuss the result of the probability of appeal in Common Court cases. Our calculations state that for 43,945 cases disposed, 1,762 were appealed. These …show more content…
The purpose of this study is to find error in judgment trends. We can assume that a reversal on a judgement is an error. In order for judgment to be reversed, it must be appealed. Therefore, we will look at the conditional property of judges that had the highest reversal on appeal in each court, P(A/R). In Common Court P(A/R), we see the mean is .16777 and the median is .12311. There is a .04466 deviation from the mean. We can attribute the differentce to the extreme values of two judges, Sallie Manzanet-Daniels with a P(A/R)=.72093 and Rosalyn H. Richter with a P(A/R)=.61111. The are our two major contributors to errors in Common …show more content…
Saxe was committing major errors in judgment. However, when we look at our table we see that the judge had three appealed cases and three that were reversed out of 5,822 disposed cases. Undoubtedly, this should not cause alarm. However, we then analyze Judge John C. Egan Jr. and noticed that out of 3,285, there were 34 cases reversed from 35 appealed, the highest in this court. Understanding this we will review the Domestic Court rankings. Our top P(A/R) went to Judge William E. McCarthy with P(A/R) =.37500 and Judge Leslie E. Stein P(A/R)=.28571. However, when we look at Judge William E. McCarthy’s trial count, 9321 and reversals of 3 on 8 appeals compared to Judge Leslie E. Stein 6,572 judgements with 6 reversals on 21 appeals, there is more to analyze. We then compare probability of reversals because this will take into account the quantity of judgements and reversals in proportional manner. We see that Judge Leslie E. Stein has the highest reversals for judgements in Domestic Court.
What we are observing is that the P(A/R) cannot denote with accuracy who is committing most errors. Quantity of disposed cases and quantity of reversal should also be taken into account. The P(A/R) is a good figure to understand the probability that a judge made a mistake on their judgement but it does not indicate what judge had the most errors. For this, we must look at the quantity of cases and their reversals in a proportionate