...Type of Submission: Case Problem “Hamilton County Judges” BUS 440 Quantitative Business Analyses Executive Summary Hamilton County Judges try thousands of cases per year. In an alarmingly large amount of these cases that are disposed, the verdict stands as rendered. Some of these cases are appealed and sometimes won or reversed. Using the resulted for 182,908 cases handled (disposed) by 38 judges in Common Pleas Court, Domestic Relations Court, and Municipal Court; Kristin DelGuzzi of the Cincinnati Enquirer conducted a study of these cases handled over a 3 year time period. Two of the judges, Dinkelacker and Hogan did not serve in the same court for the entire 3 year period. The purpose of the newspapers study was to evaluate the performance of these judges. Appeals are often caused by mistakes made by judges and the newspaper wanted to find out which judges were doing a good and bad jobs. Contents PROBLEM DEFINITION 5 MODEL VERIFICATION 14 OPTIMIZATION AND DECISION MAKING 15 MODEL COMMUNICATION TO MANAGEMENT 16 MODEL IMPLEMENTATION 16 Bibliography 17 PROBLEM DEFINITION Hamilton County Judges try thousands of cases per year. In an alarmingly large amount of these cases that are disposed, the verdict stands as rendered. Some of these cases are appealed and sometimes won or reversed. Using the resulted for 182,908 cases handled (disposed) by 38 judges in Common Pleas Court, Domestic Relations Court, and Municipal Court; Kristin DelGuzzi of the Cincinnati...
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...June 20, 2011 Case Study #3 Case Problem: Hamilton County Judges Three major court systems in Hamilton County were reviewed in depth, and case information from the Common Pleas, Domestic Relations, and Municipal Courts were reviewed. This study compiles information from 38 Judges who had a total of 182,908 cases presented to them over a three year period. This study shows the number of cases that were disposed, appealed, and reversed. This study is to aid in determining which judges have a greater proficiency trying cases and their verdicts stand as rendered, rather than the verdicts being appealed or reversed. Each judges case load was reviewed and the statistics were determined by how many cases have been appealed, reversed or a conjunction of both. This information will help determine the judges who have made the least, as well as the most errors, while serving in the Hamilton County Court System over the three year period. This study will show that for all the disposed cases in the Hamilton County Court System during the 3 year evaluation period, the Common Pleas Court the probability of a case being appealed and reversed is 0.1129 (11.29%); Domestic Relations Courts probability of a case being appealed and reversed is 0.1604 (16.04%); Municipal Court probability of a case being appealed and reversed is 0.2080(20.80%). The probability of a case being appealed, per judge is: (P) indicating Probability Common Pleas Court Judges: (P) of Appeal per Judge (P) of...
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...Hamilton County Judges try thousands of cases per year. This study is to provide the newspaper with how well the judges are performing. With the results of Kristen DelGuzzie of the Cincinnati Enquirer that conducted the study of the cases in Hamilton County for a three year period. Providing analytical results on how well each and every judge is doing. With the results, the Cincinnati Enquirer will be able answer the question of which judge is performing a good job and which is not performing a good job. By evaluating the results from the data collects. The company of Annette is hired to assist in the data analysis. Case: Hamilton County Judges A Review by the Company of Annette Over a period of three years, Kristen DelGuzzi of the Cincinnati Enquirer created a study to see which Judges were performing the best and worst. Appeals are the result of a mistake made by the judges. Disposed is when the judge throws out the case. And Reversed is when the judge reverses what was said during a pervious case. With this study I will being answering the following questions: 1. Who is doing a good job? 2. Who isn’t doing a good job? 3. Why does the company of Annette think so? With answering the questions. This report will also provide the results from: * The probability of cases being appealed and reversed in three different courts * The probability of a case being appealed for each judge * The probability of a case being reversed for each judge * Rank the judges within each...
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...Hamilton County Judges Effectiveness Study Prepared by Team 32 Prepared for Dr. Norman Lewis BA 2300 Statistics 1 This study is designed to provide the efficiency status of 38 Hamilton County Judges. The study looked at the number of cases disposed, appealed and reversed. The information gathered is from data for the Common Pleas Court, Domestic Relations Court and Municipal Court. Two of the judges, Patrick Dinkelacker and Timothy Hogan served in two different courts during the three year study period. This report will show the efficiency of all 38 judges as a whole and as individuals. There were 182,908 total cases disposed during the study with 2,368 were appealed and 320 decisions being reversed. Based on the data provided in the Hamilton County Judges study the following probabilities were found: A. Common Pleas Court disposed 43,945 cases disposed equaling 24% 1,762 cases appealed equaling 4.01% 199 cases reversed equaling .49% B. Domestic Relations Court 30,499 cases disposed equaling 17% 106 cases appealed equaling 3.36% 17 cases reversed equaling .06% C. Municipal Court 108,908 cases disposed equaling 59% 500 cases appealed equaling .44% 104 cases reversed equaling .09% Court Cases Common Court 24% Municipal Court 59% Domestic Court 17% Distribution of Total Cases Disposed by Court The probability of appeal by judge for each court is as follows: A. Common Pleas Court Judge Fred Cartolano Thomas Crush Patrick Dinkelacker Timothy Hogan Robert Kraft...
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.... Use the sales forecaster’s predication to describe a normal probability distribution that can be used to approximate the demand distribution. Sketch the distribution and show its mean and standard deviation. Let's assume that the expected sales distribution is normally distributed, with a mean of 20,000, and 95% falling within 10,000 and 20,000. We know that +/- 1.96 standard deviations from the mean will contain 95% of the values. So, we can get the standard deviation by: z = (x - mu)/sigma = 1.96 sigma = (x - mu)/z Sigma = (30,000-20,000) / 1.96 = 5,102 units. So, we have a distribution with a mean of 20,000 and a standard deviation of 5,102. 2. Compute the probability of a stock-out for the order quantities suggested by members of the management team. Using the normal distribution theory, we discover that as the ordered quantity increases the probability of stockout decreases. At 15,000 the probability of stockout will be 0.8365 At 18,000 the probability of stockout will be 0.6517 At 24,000 the probability of stockout will be 0.2177 At 28,000 the probability of stockout will be 0.0582 3. Compute the projected profit for the order quantities suggested by the management team under three scenarios: worst case in which sales = 10,000 units, most likely case in which sales = 20,000 units and best case in which sales = 30,000 units: Order Quantity: 15,000 were cost price is $16, selling price $24 & after holiday selling price $5 |Unit Sales...
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...Probability and statistics are two related but separate academic disciplines. Statistical analysis often uses probability distributions, and the two topics are often studied together. However, probability theory contains much that is of mostly of mathematical interest and not directly relevant to statistics. Moreover, many topics in statistics are independent of probability theory. Probability (or likelihood) is a measure or estimation of how likely it is that something will happen or that a statement is true. Probabilities are given a value between 0 (0% chance or will not happen) and 1 (100% chance or will happen). The higher the degree of probability, the more likely the event is to happen, or, in a longer series of samples, the greater the number of times such event is expected to happen. These concepts have been given an axiomatic mathematical derivation in probability theory (see probability axioms), which is used widely in such areas of study as mathematics, statistics, finance, gambling, science, artificial intelligence/machine learning and philosophy to, for example, draw inferences about the expected frequency of events. Probability theory is also used to describe the underlying mechanics and regularities of complex systems. Statistics is the study of the collection, organization, analysis, interpretation and presentation of data. It deals with all aspects of data, including the planning of data collection in terms of the design of surveys and experiments. The word statistics...
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...Case Study 1 – Hamilton County Judges 1. Based on the information provided in the Hamilton County Judges’ case study, the probability of cases being appealed and reversed in the three different courts are as follows: a. For the total cases disposed in the Common Pleas Court there is a 0.1129 probability of a case being appealed and reversed. b. For the total cases disposed in the Domestic Relations Court there is a 0.1604 probability of a case being appealed and reversed. c. For the total cases disposed in the Municipal Court there is a 0.2080 probability of a case being appealed and reversed. 2. The probability of a case being appealed, per judge, is: a. Common Pleas Court: Judge | (P) of Appeal | Fred Cartolano | 0.045110 | Thomas Crush | 0.035291 | Patrick Dinkelacker | 0.034976 | Timothy Hogan | 0.030706 | Robert Kraft | 0.040472 | William Mathews | 0.040194 | William Morrissey | 0.039908 | Norbert Nadel | 0.044272 | Arthur Ney Jr. | 0.038832 | Richard Niehaus | 0.040859 | Thomas Nurre | 0.040333 | John O'Connor | 0.043449 | Robert Ruehlman | 0.045242 | J. Howard Sundermann Jr. | 0.062827 | Ann Marie Tracey | 0.040433 | Ralph Winkler | 0.028488 | b. Domestic Relations Court: Judge | (P) of Appeal | Penelope Cunningham | 0.002565 | Patrick Dinkelacker | 0.003166 | Deborah Gaines | 0.005455 | Ronald Panioto | 0.002467 | c. Municipal Court: Judge | (P) of Appeal...
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...Clayton, VIC 3800 Aaron.Nicholas@buseco.monash.edu.au ABSTRACT This paper examines the probability of a recent university graduate obtaining full-time employment by degree of study. It allows for degree choice to be endogenous (self-selection bias) and adjusts for those graduates not in the labour force who are not typically considered in graduate outcome studies (sample-selection bias). The self-selection problem is able to be identified by using a unique data set that combines data from the 2005 and 2006 Australian Graduate Destination Survey with data from the University of Tasmania’s (UTAS) student administration database, which includes students’ pre-tertiary school results. Degree choice is modelled using a Nested Logit, while labour force participation is modelled using a Probit. Using a ‘Heckit’ type methodology, the Inverse Mills Ratios (pseudo-residuals) from the Nested Logit and the modified Inverse Mills Ratios from the Probit are included in the final Probit model for Employment. Both correction terms are statistically significant at 5% in the employment probability equation. Allowing for self selection significantly reduces the probability of employment for accounting, architecture, engineering and economics/finance graduates by 6%, 9%, 10% and 5% respectively, suggesting that better students select these degrees at UTAS. Correcting for sample selection reduces the probability of employment for the average student from 80% to 70%,...
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...county judges try thousands of cases per year. In an overwhelming majority of the cases disposed, the verdict stands as rendered. However, some cases are appealed, and of those appealed, some of the cases are reversed. Kristen DelGuzzi of The Cincinnati Enquirer conducted a study of cases handled by Hamilton county judges over a three-year period. The data is in the file Judge. It contains results for 182,908 cases handled (disposed) by 38 judges in the Common Pleas Court, Domestic Relations Court and Municipal Court. Two of the judges (Dinkelacker and Hogan) did not serve in the same court for the entire three year period. The purpose of the newspaper’s study was to evaluate the performance of the judges. Appeals are often a result of mistakes made by the judges, and the newspaper wanted to know which judges were doing a good job and which were making too many mistakes. You are called on to assist in the data analysis. Use your knowledge of probability and conditional probability to help with the ranking of judges. You may be able to analyze the likelihood of appeal and reversal for cases handled by different judges. Managerial Report: Prepare a report with your rankings of the judges. Also, include an analysis of the likelihood of appeal and case reversal in the three courts. At a minimum, your report should include the following: 1. The probability of cases being appealed and reversed in the three different courts. 2. The probability of a case being appealed for each judge...
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...CASE STUDY: 1 The bulbs manufactured by a company gave a mean life of 3000 hours with standard deviation of 400 hours. If a bulb is selected at random, what is the probability it will have a mean life less than 2000 hours? Question: 1) Calculate the probability. 2) In what situation does one need probability theory? 3) Define the concept of sample space, sample points and events in context of probability theory. 4) What is the difference between objective and subjective probability? CASE STUDY : 2 The price P per unit at which a company can sell all that it produces is given by the function P(x) = 300 — 4x. The cost function is c(x) = 500 + 28x where x is the number of units produced. Find x so that the profit is maximum. Question: 1) Find the value of x. 2) In using regression analysis for making predictions what are the assumptions involved. 3) What is a simple linear regression model? 4) What is a scatter diagram method? CASE STUDY : 3 Mr Sehwag invests Rs 2000 every year with a company, which pays interest at 10% p.a. He allows his deposit to accumulate at C.I. Find the amount to the credit of the person at the end of 5th year. Question : 1) What is the Time Value of Money concept. 2) What do you mean by present value of money? 3) What is the Future Value of money. 4) What the amount to be credited at the end of 5th year. CASE STUDY : 4 The cost of fuel in running of an engine...
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...h J. Barnett Mr. W. Gissy Econ 2300/05 February 22, 2005 Case Study 1 – Hamilton County Judges 1. Based on the information provided in the Hamilton County Judges’ case study, the probability of cases being appealed and reversed in the three different courts are: a. For the total cases disposed in the Common Pleas Court there is a 0.1129 probability of a case being appealed and reversed. b. For the total cases disposed in the Domestic Relations Court there is a 0.1604 probability of a case being appealed and reversed. c. For the total cases disposed in the Municipal Court there is a 0.2080 probability of a case being appealed and reversed. 2. The probability of a case being appealed, per judge, is: a. Common Pleas Court: Judge Fred Cartolano Thomas Crush Patrick Dinkelacker Timothy Hogan Robert Kraft William Mathews William Morrissey Norbert Nadel Arthur Ney Jr. Richard Niehaus Thomas Nurre John O'Connor Robert Ruehlman J. Howard Sundermann Jr. Ann Marie Tracey Ralph Winkler b. Domestic Relations Court: Judge Penelope Cunningham Patrick Dinkelacker Deborah Gaines Ronald Panioto (P) of Appeal per Judge 0.002565 0.003166 0.005455 0.002467 (P) of Appeal per Judge 0.045110 0.035291 0.034976 0.030706 0.040472 0.040194 0.039908 0.044272 0.038832 0.040859 0.040333 0.043449 0.045242 0.062827 0.040433 0.028488 Barnett 2 c. Municipal Court: Judge Mike Allen Nadine Allen Timothy Black David Davis Leslie Isaiah Gaines Karla Grady Deidra Hair Dennis Helmick Timothy Hogan James Patrick...
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...14. Data analysis and interpretation Concepts and techniques for managing, editing, analyzing and interpreting data from epidemiologic studies. Key concepts/expectations This chapter contains a great deal of material and goes beyond what you are expected to learn for this course (i.e., for examination questions). However, statistical issues pervade epidemiologic studies, and you may find some of the material that follows of use as you read the literature. So if you find that you are getting lost and begin to wonder what points you are expected to learn, please refer to the following list of concepts we expect you to know: Need to edit data before serious analysis and to catch errors as soon as possible. Options for data cleaning – range checks, consistency checks – and what these can (and can not) accomplish. What is meant by data coding and why is it carried out. Basic meaning of various terms used to characterize the mathematical attributes of different kinds of variables, i.e., nominal, dichotomous, categorical, ordinal, measurement, count, discrete, interval, ratio, continuous. Be able to recognize examples of different kinds of variables and advantages/disadvantages of treating them in different ways. What is meant by a “derived” variable and different types of derived variables. Objectives of statistical hypothesis tests (“significance” tests), the meaning of the outcomes from such tests, and how to interpret a p-value...
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...Assignment #1: JET Copies Case Problem Strayer University MAT540: Quantitative Methods October 29, 2013 JET Copies is a company designed to alleviate a longer commute and longer wait time, and possibly have a more cost efficient method for the college students to make copies. The three students James, Ernie, and Terri decided to go into business together with a copying business initiative. Considering what was ahead of the new business, for example, possible machine downtime and days to repair the copier, they had to determine the average number of days that it would take for them to acquire a repair team to fix the machine in the event that it broke down. As discovered, the average time for repair was between one and four days. In order to calculate the average, a probability distribution was developed using Microsoft Excel. From there, the cumulative probability was obtained by adding the probability, P(x), from the previously itemized probabilities where the cumulative summation of a probability is always equal to one (1) or 100%. A random number formula, =RAND(), was plugged into the Microsoft Excel desired cell, in this situation, (H4), which generated a random range of numbers that are greater than or equal to zero and less than one. The interim time between breakdowns were achieved simply by soliciting the experience several staff members in the college of business who were familiar with frequency of the copier’s inconsistent behavior. It was estimated that the...
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...uvapub:57876 Filename WP11.pdf Version unknown SOURCE (OR PART OF THE FOLLOWING SOURCE): Type report Title Tax evasion and the source of income : an experimental study in Albania and the Netherlands Author(s) K. Gërxhani, A. Schram Faculty UvA: Universiteitsbibliotheek Year 2003 FULL BIBLIOGRAPHIC DETAILS: http://hdl.handle.net/11245/1.427430 Copyright It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content licence (like Creative Commons). UvA-DARE is a service provided by the library of the University of Amsterdam (http://dare.uva.nl) (pagedate: 2014-11-27)TAX EVASION AND THE SOURCE OF INCOME: AN EXPERIMENTAL STUDY IN ALBANIA AND THE NETHERLANDS AIAS Working Paper 03/11 May 2003 Dr. Klarita Gërxhani AMSTERDAM INSTITUTE FOR Prof. Dr. Arthur Schram ADVANCED LABOUR STUDIES Universiteit van Amsterdam © Klarita Gërxhani Amsterdam, May 2003 This paper can be downloaded at www.uva-aias.net/files/aias/WP11.pdf Amsterdam Institute for Advanced Labour Studies Tax Evasion and the Source of Income: An Experimental Study in Albania and the Netherlands 5 Tax Evasion and the Source of Income: An Experimental Study in Albania and the Netherlands∗ Abstract A series of experiments among different social groups in both Albania and the Netherlands give the opportunity to compare behavioral...
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...Running head: Probability of Appeals and Reversals Probability of Appeals and Reversals Jackson County Judges Debra R. Hunter CSU Global Campus Math 410-Quantitative Business Analysis Jose Romero Instructor 03/08/2015 Probability of Appeals and Reversals Jackson County Judges The Problem Using a problem given to us in our study of Quantitative Business Analysis an excel spreadsheet has been created in order to answer the given questions. Following is the given problem. 1. The probability of cases being appealed in each of the three different courts. 2. The probability of cases being reversed in each of the three different courts. 3. The probability of cases being reversed given an appeal in each of the three different courts. 4. The probability of a case being appealed for each judge. 5. The probability of a case being reversed for each judge. 6. The probability of reversal, given an appeal for each judge. After these six questions have been answered then a ranking of the judges can be accomplished. The numbers being used in each of the calculations is coming from the excel worksheet that is attached. The last question of the given problem follows. Rank the judges within each court for each of the probabilities in 4 - 6. Then, find the sum of the ranks and get an overall ranking for each judge. Evaluate and discuss the meaning of your results. Results The following results are based on the calculations found...
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