The purpose of this assignment is to know how to apply probability concepts to evaluate judges’ performance. See table below Calculate the probability of cases being appealed and reversed in the three different courts. Calculate the probability of a case being appealed for each judge. Calculate the probability of a case being reversed for each judge. Judge Disposed Appealed Reversed Court Fred Cartolano 3037 137 12 Common Thomas Crush 3372 119 10 Common Patrick Dinkelacker 1258 44 8 Common Timothy Hogan 1954 60 7 Common Robert Kraft 3138 127 7 Common William Mathews 2264 91 18 Common William Morrissey 3032 121 22 Common Norbert Nadel 2959 131 20 Common Arthur Ney Jr. 3219 125 14 Common Richard Niehaus 3353 137 16 Common Thomas Nurre 3000 121 6 Common John O'Connor 2969 129 12 Common Robert Ruehlman 3205 145 18 Common J. Howard Sundermann Jr. 955 60 10 Common Ann Marie Tracey 3141 127 13 Common Ralph Winkler 3089 88 6 Common Penelope Cunningham 2729 7 1 Domestic Patrick Dinkelacker 6001 19 4 Domestic Deborah Gaines 8799 48 9 Domestic Ronald Panioto 12970 32 3 Domestic Mike Allen 6149 43 4 Muni Nadine Allen 7812 34 6 Muni Timothy Black 7954 41 6 Muni David Davis 7736 43 5 Muni Leslie Isaiah Gaines 5282 35 13 Muni Karla Grady 5253 6 0 Muni Deidra Hair 2532 5 0 Muni Dennis Helmick 7900 29 5 Muni Timothy Hogan 2308 13 2 Muni James Patrick Kenney 2798 6 1 Muni Joseph Luebbers 4698 25 8 Muni William Mallory 8277 38 9 Muni Melba Marsh 8219 34 7 Muni Beth Mattingly 2971 13 1 Muni Albert Mestemaker 4975 28 9 Muni Mark Painter 2239 7 3 Muni Jack Rosen 7790 41 13 Muni Mark Schweikert 5403 33 6 Muni David Stockdale 5371 22 4 Muni John A. West 2797 4 2 Muni
The purpose of this assignment is to know how to apply probability concepts to evaluate judges’ performance. See table below Calculate the probability of cases being appealed and reversed in the three different courts. Calculate the probability of a case being appealed for each judge. Calculate the probability of a case being reversed for each judge. Judge Disposed Appealed Reversed Court Fred Cartolano 3037 137 12 Common Thomas Crush 3372 119 10 Common Patrick Dinkelacker 1258 44 8 Common Timothy Hogan 1954 60 7 Common Robert Kraft 3138 127 7 Common William Mathews 2264 91 18 Common William Morrissey 3032 121 22 Common Norbert Nadel 2959 131 20 Common Arthur Ney Jr. 3219 125 14 Common Richard Niehaus 3353 137 16 Common Thomas Nurre 3000 121 6 Common John O'Connor 2969 129 12 Common Robert Ruehlman 3205 145 18 Common J. Howard Sundermann Jr. 955 60 10 Common Ann Marie Tracey 3141 127 13 Common Ralph Winkler 3089 88 6 Common Penelope Cunningham 2729 7 1 Domestic Patrick Dinkelacker 6001 19 4 Domestic Deborah Gaines 8799 48 9 Domestic Ronald Panioto 12970 32 3 Domestic Mike Allen 6149 43 4 Muni Nadine Allen 7812 34 6 Muni Timothy Black 7954 41 6 Muni David Davis 7736 43 5 Muni Leslie Isaiah Gaines 5282 35 13 Muni Karla Grady 5253 6 0 Muni Deidra Hair 2532 5 0 Muni Dennis Helmick 7900 29 5 Muni Timothy Hogan 2308 13 2 Muni James Patrick Kenney 2798 6 1 Muni Joseph Luebbers 4698 25 8 Muni William Mallory 8277 38 9 Muni Melba Marsh 8219 34 7 Muni Beth Mattingly 2971 13 1 Muni Albert Mestemaker 4975 28 9 Muni Mark Painter 2239 7 3 Muni Jack Rosen 7790 41 13 Muni Mark Schweikert 5403 33 6 Muni David Stockdale 5371 22 4 Muni John A. West 2797 4 2 Muni
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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The purpose of this assignment is to know how to apply probability concepts to evaluate judges’ performance.
See table below
- Calculate the probability of cases being appealed and reversed in the three different courts.
- Calculate the probability of a case being appealed for each judge.
- Calculate the probability of a case being reversed for each judge.
Judge | Disposed | Appealed | Reversed | Court |
Fred Cartolano | 3037 | 137 | 12 | Common |
Thomas Crush | 3372 | 119 | 10 | Common |
Patrick Dinkelacker | 1258 | 44 | 8 | Common |
Timothy Hogan | 1954 | 60 | 7 | Common |
Robert Kraft | 3138 | 127 | 7 | Common |
William Mathews | 2264 | 91 | 18 | Common |
William Morrissey | 3032 | 121 | 22 | Common |
Norbert Nadel | 2959 | 131 | 20 | Common |
Arthur Ney Jr. | 3219 | 125 | 14 | Common |
Richard Niehaus | 3353 | 137 | 16 | Common |
Thomas Nurre | 3000 | 121 | 6 | Common |
John O'Connor | 2969 | 129 | 12 | Common |
Robert Ruehlman | 3205 | 145 | 18 | Common |
J. Howard Sundermann Jr. | 955 | 60 | 10 | Common |
Ann Marie Tracey | 3141 | 127 | 13 | Common |
Ralph Winkler | 3089 | 88 | 6 | Common |
Penelope Cunningham | 2729 | 7 | 1 | Domestic |
Patrick Dinkelacker | 6001 | 19 | 4 | Domestic |
Deborah Gaines | 8799 | 48 | 9 | Domestic |
Ronald Panioto | 12970 | 32 | 3 | Domestic |
Mike Allen | 6149 | 43 | 4 | Muni |
Nadine Allen | 7812 | 34 | 6 | Muni |
Timothy Black | 7954 | 41 | 6 | Muni |
David Davis | 7736 | 43 | 5 | Muni |
Leslie Isaiah Gaines | 5282 | 35 | 13 | Muni |
Karla Grady | 5253 | 6 | 0 | Muni |
Deidra Hair | 2532 | 5 | 0 | Muni |
Dennis Helmick | 7900 | 29 | 5 | Muni |
Timothy Hogan | 2308 | 13 | 2 | Muni |
James Patrick Kenney | 2798 | 6 | 1 | Muni |
Joseph Luebbers | 4698 | 25 | 8 | Muni |
William Mallory | 8277 | 38 | 9 | Muni |
Melba Marsh | 8219 | 34 | 7 | Muni |
Beth Mattingly | 2971 | 13 | 1 | Muni |
Albert Mestemaker | 4975 | 28 | 9 | Muni |
Mark Painter | 2239 | 7 | 3 | Muni |
Jack Rosen | 7790 | 41 | 13 | Muni |
Mark Schweikert | 5403 | 33 | 6 | Muni |
David Stockdale | 5371 | 22 | 4 | Muni |
John A. West | 2797 | 4 | 2 | Muni |
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