Study of Asia-Pacific MBA Programs
Bloomberg Business week posted an article on March 17th 2014 titled, Elite Business Schools Hike Tuition for the Class of 2016. This article draws a comparison between tuition costs for the class of 2015 for selected US MBA programs and the class of 2016. Tuition costs are increasing more and more every year, for this reason looking at other alternatives may be more cost effective. The following study provides and interpretation of tuition cots both local and foreign in the Asia-Pacific region. From this study we can see the comparison between tuition costs and starting salaries. We can also see other deciding factors such as admission requirements. Finally this study provides a recommendation for an MBA program in the Asia-Pacific region. Please note Table 1.1 listing the study’s programs with their correlating graph ID.

Table 1.1 Business School | Graph ID | Lahore University of Management Sciences | LUMS | Indian Institute of Management (Calcutta) | IIMC | University of New South Wales (Sydney) | UNSW | Indian Institute of Management (Bangalore) | IIMB | Curtin Institute of Technology (Perth) | CIT | Massey University (Palmerston North, New Zealand) | MU | University of Queensland (Brisbane) | UQ | University of Adelaide | UA | Monash Mt. Eliza Business School (Melbourne) | MMEBS | Melbourne Business School | MBS | Royal Melbourne Institute of Technology | RMIT | Macquarie Graduate School of Management (Sydney) | MGSM | Asian Institute of Management (Manila) | AIMM | National University of Singapore | NUS | De La Salle University (Manila) | DLSU | Jamnalal Bajaj Institute of Management Studies (Bombay) | JBIMS | Universiti Sains Malaysia (Penang) | USM | Indian Institute of Management (Ahmedabad) | IIMA | Nanyang Technological University (Singapore) | NTU | Chinese University of Hong Kong | CU | Hong Kong University of Science and Technology | HKUST | Chulalongkorn University (Bangkok) | CU | Asian Institute of Management (Bangkok) | AIMB | Australian National University (Canberra) | ANU | International University of Japan (Niigata) | IUJ |

Summary:
On average there are about 165 full time students enrolled in Asia-Pacific business schools. Of these the schools, the one with the least amount of students is Macquarie Graduate School of Management in Sydney with 12 full-time students and the school with the largest amount of students is Indian Institute of Management in Calcutta with 463 enrollees. Most of the schools have about 30 full-time enrollees.
These MBA programs have an average of 8-9 students per faculty ratio and most programs have 5 students per faculty. The University of Adelaide has the highest student per faculty ratio at 19 to 1 while Hong Kong University of Science and Technology has the lowest student per faculty ratio of 2 to 1.
The Asia-Pacific business schools range in local tuition with the lowest tuition program at $1,000 to the highest at $33,060. The typical program will run about $12,375 year. Foreign tuition while more expensive in some areas does not differ greatly from the local tuition prices. The average cost for a foreign tuition is $16,582 while the highest tuition charge is $33,060 which is at International University of Japan in Niigata charges the same for Local and Foreign tuition in comparison to the rest of the programs. When evaluating the age and nationality of the enrollees we see that most enrollees at the Asia-Pacific business schools are 28 years of age and that on average 28% of the students enrolled in these MBA programs are from other countries. The ages range from the oldest at 37 years old to the youngest at 22 years of age. These MBA programs for the most part have a percentage of foreign student attendance. In the Asian Institute of Management in Bangkok, 90% of those enrolled are foreign students while 3 out of the 25 programs have no foreign enrollment. Regarding requirements for admittance into the Asia-Pacific Business Schools 56% of the schools require a GMAT exam while 44% do not, we can deduce that in this region we can easily find schools that do not require a GMAT exam at all. In addition 32% of the programs require an English test and 74% of the schools require work experience. Starting salaries range greatly among these schools with the minimum starting salary at $7,000 and the maximum at $87,000. Coincidentally, the International University of Japan in Niigata, the school with the highest tuition at $33,060 also has the highest starting salary at $87,000. In reviewing the given data set we can easily determine the range of tuition both local and foreign. Using descriptive statistics allows us to see things like how important it is to have work experience, confirms that local tuition tends to be cheaper than foreign tuition in some areas, and helps us make a better decision based on the student to faculty ratio. Comparison of Local and Foreign tuition costs: 15 out of the 25 schools charge a higher foreign tuition while the other 10 schools charge the same for local and foreign students. Graph 1.1 shows the difference in cost between the local and foreign tuition. The Indian Institute of Management in Calcutta has the largest percent difference between local and foreign tuition costs at 82% while De La Salle University in Manila has an 8% difference which is insignificant.

Graph 1.1 Starting salaries vary greatly between the schools that require work experience and those that do not. The data for the starting salaries of schools that do not require work experience list a couple of outliers that increase the average significantly to $24,583. The Chinese University of Hong Kong reports a starting salary of $31,000 and the International University of Japan in Niigata lists at $87,000 for a starting salary. Without these outliers the mean of the starting salaries for the schools not requiring work experience would be $7,375, this is a 70% difference. This can be seen graph 1.2 where most of the schools that do not require work experience report a starting salary below $10,000 with the exception of the aforementioned. Schools that require work experience on average have a starting salary of $41,305. Graph 1.2 Starting Salaries Based on English Test Requirements: It can be deduced from the data that if a student has a difficult time with English they will be able to find an Asia-Pacific school that does not require an English test. Only 8 out of the 25 schools require an English test and 17 do not. Of the 17 schools that do not require an English test, the average starting salary is $33,624. However, should the candidate have strong English skills, the average starting salary of the schools that do require an English test is $45,088, this higher mean is due to the fact that The International University of Japan in Niigata requires an English test and their starting salary is listed at $87,000 which increases the mean. If the International University of Japan in Niigata were not a part of the data set the average starting salary of the schools that require an English test would be $39,100 which is very close to the average starting salary of the schools that do not require an English Test. Graph 1.3 shows this comparison. Graph 1.3

The Relation between Tuition and Starting Salary:
In some cases a higher tuition cost comes with a very high starting salary such as with the International University of Japan in Niigata where the local and foreign tuition cost is $33,060 and the starting salary is $87,000. The same goes for Melbourne Business School where the local and foreign tuition cost are close, $24,420 and $29,600 respectively and the starting salary is $71,400. However, when looking at Chulalongkorn University in Bangkok, we find that the cost of local and foreign tuition is similar to the starting salary, local and foreign tuition is $17,355 and the starting salary $17,600, in this particular case the student would be making about the same as their cost of tuition. Furthermore, Curtin Institute of Technology in Perth has a relatively low cost of local tuition of $9,475 and one of the higher starting salaries at $55,000. With the exception of the Indian Institute of Management in both Calcutta and Bangalore and Lahore University of Management Sciences (see table 1.2) we can say that students can expect to receive an equal or higher starting salary in comparison to their tuition cost. Graph 1.4 shows the comparison between tuition costs, both local and foreign and their corresponding starting salaries.
Table 1.2 Business School | Local Tuition | Foreign Tuition | Starting Salary | Indian Institute of Management (Calcutta) | 2,880 | 16,000 | 7,400 | Indian Institute of Management (Bangalore) | 3,935 | 16,000 | 7,500 | Lahore University of Management Sciences | 11,250 | 26,300 | 7,500 |

Graph 1.4

Bloomberg Business week, www.businessweek.com ranks the top 10 full time MBA programs in the United States. The 10th in rank, The University of Virginia, costs $95,900. Harvard University’s MBA program, ranked 2nd, costs $126,576. After studying the data regarding Asia-Pacific schools, in terms of tuition costs there are several programs to choose from that are inexpensive in comparison to American Business schools and with small student per faculty ratio. The criteria to follow when choosing a business school in the Asia-Pacific region would be to study the schools with the highest starting salaries and the lowest student to faculty ratio. Graph 1.5 shows this criteria. Table 1.2 lists the recommendations.

Graph 1.5

Table 1.3 Business School | Graph ID | Students per Faculty | Local Tuition ($) | Foreign Tuition ($) | Starting Salary ($) | University of New South Wales (Sydney) | UNSW | 4 | 19,993 | 32,582 | 65,200 | Melbourne Business School | MBS | 5 | 24,420 | 29,600 | 71,400 | Nanyang Technological University (Singapore) | NTU | 5 | 8,500 | 8,500 | 49,300 | Chinese University of Hong Kong | CU | 5 | 11,140 | 11,140 | 31,000 | Hong Kong University of Science and Technology | HKUST | 2 | 11,513 | 11,513 | 34,000 | Australian National University (Canberra) | ANU | 2 | 20,300 | 20,300 | 46,600 | International University of Japan (Niigata) | IUJ | 4 | 33,060 | 33,060 | 87,000 |

Evaluation of Hamilton County Judges
In studying the cases tried by the Hamilton County judges we will show the likelihood of cases being appealed in this county and of the cases being appealed, the probability of these cases being reversed. It is important to note that in Hamilton County most disposed cases are not reversed, the verdict remains. This evaluation rates judges by assigning a grade and ranking them by said grade.
There were 183,727 disposed cases in Hamilton County of these cases 2,416 were appealed and out of the appealed 301 cases were reversed. Out of the 183,727 cases the likelihood of a case being appealed is very low at .16 of a percent furthermore the likelihood of an appealed case to be reversed is 12.46%. When viewing these statistics in the individual courts, Common Pleas Court, Domestic Relations Court, and Municipal Court we find that most of the appealed cases are in the Common Pleas Court. The likelihood of a case being appealed in the Common Pleas Court is about 4% and of those about 10% of the cases are reversed. In comparison the likelihood of a case being appealed in the Municipal Court if only about .5% but the likelihood of these cases being reversed is higher than in any of the other courts at 19.37%. Table 2.1 | | % Appealed | % Reversed | % Reversed when Appealed | Total Number of Cases Disposed | 183727 | 1.31% | 0.16% | 12.46% | Total Number of Appealed | 2416 | | | | Total Number of Reversed | 301 | | | | Total Number of Cases (Common) | 44472 | 4.00% | 0.40% | 10.07% | Total Number of Cases Appealed (Common) | 1777 | | | | Total Number of Cases Reversed (Common) | 179 | | | | Total Number of Cases (Domestic) | 29556 | 0.35% | 0.06% | 17.65% | Total Number of Cases Appealed (Domestic) | 102 | | | | Total Number of Cases Reversed (Domestic) | 18 | | | | Total Number of Cases (Muni) | 109699 | 0.49% | 0.09% | 19.37% | Total Number of Cases Appealed (Muni) | 537 | | | | Total Number of Cases Reversed (Muni) | 104 | | | |

We can rank the individual judges based on the percentage of cases that were appealed paying close attention to the percentage of cases reversed, noting that a judge may have had a number of cases appealed but not all of these would have been reversed. Table 2.2 shows the ranking of judges based on percent of cases appealed. Judge Karla Grady proves to have the lowest percentage of cases appealed at 0.11% and of these cases 0% were reversed. Judge J. Howard Sundermann Jr. disposed 955 cases and highest number of cases appealed at 6.28%, of these 16.67% were reversed. It is important to look at the amount of cases these judges disposed. Judge Grady disposed 5253 while Judge Sundermann disposed 955, the average number of cases disposed was 4,834. From this we can conclude that judge Sundermann disposed a low number of cases but a high number of those cases in comparison to the other judges was appealed. Judge Sundermann however, did not have the highest percentage of reversed cases, Judge Mark Painter disposed 2,239 cases of which 0.4% were appealed and 55.55% of those appealed were reversed.

Table 2.2 Judge | Disposed | Appealed | Reversed | Court | The Percentage of cases that were appealed | The Percentage of cases that were reversed | The Percentage of Cases Appealed that were Reversed | Karla Grady | 5253 | 6 | 0 | Muni | 0.1142% | 0.0000% | 0.0000% | Deidra Hair | 2532 | 5 | 0 | Muni | 0.1975% | 0.0000% | 0.0000% | James Patrick Kenney | 2798 | 6 | 1 | Muni | 0.2144% | 0.0357% | 16.6667% | Ronald Panioto | 12970 | 32 | 3 | Domestic | 0.2467% | 0.0231% | 9.3750% | Dennis Helmick | 7712 | 29 | 5 | Muni | 0.3760% | 0.0648% | 17.2414% | Mark Painter | 2239 | 9 | 5 | Muni | 0.4020% | 0.2233% | 55.5556% | David Stockdale | 5371 | 22 | 4 | Muni | 0.4096% | 0.0745% | 18.1818% | Melba Marsh | 8219 | 34 | 7 | Muni | 0.4137% | 0.0852% | 20.5882% | Nadine Allen | 7812 | 34 | 6 | Muni | 0.4352% | 0.0768% | 17.6471% | Beth Mattingly | 2971 | 13 | 1 | Muni | 0.4376% | 0.0337% | 7.6923% | Deborah Gaines | 8277 | 38 | 9 | Domestic | 0.4591% | 0.1087% | 23.6842% | John A. West | 2797 | 13 | 3 | Muni | 0.4648% | 0.1073% | 23.0769% | Joseph Luebbers | 5178 | 25 | 8 | Muni | 0.4828% | 0.1545% | 32.0000% | Timothy Black | 7954 | 41 | 6 | Muni | 0.5155% | 0.0754% | 14.6341% | Jack Rosen | 7790 | 41 | 13 | Muni | 0.5263% | 0.1669% | 31.7073% | William Mallory | 8799 | 48 | 9 | Muni | 0.5455% | 0.1023% | 18.7500% | David Davis | 7736 | 43 | 5 | Muni | 0.5558% | 0.0646% | 11.6279% | Albert Mestemaker | 4975 | 28 | 9 | Muni | 0.5628% | 0.1809% | 32.1429% | Penelope Cunningham | 2308 | 13 | 2 | Domestic | 0.5633% | 0.0867% | 15.3846% | Leslie Isaiah Gaines | 5282 | 35 | 13 | Muni | 0.6626% | 0.2461% | 37.1429% | Mike Allen | 6149 | 43 | 4 | Muni | 0.6993% | 0.0651% | 9.3023% | Patrick Dinkelacker | 7259 | 63 | 12 | Domestic | 0.8679% | 0.1653% | 19.0476% | Mark Schweikert | 5403 | 55 | 4 | Muni | 1.0180% | 0.0740% | 7.2727% | Timothy Hogan | 4683 | 67 | 8 | Muni | 1.4307% | 0.1708% | 11.9403% | Thomas Crush | 3372 | 89 | 6 | Common | 2.6394% | 0.1779% | 6.7416% | Ralph Winkler | 3089 | 88 | 6 | Common | 2.8488% | 0.1942% | 6.8182% | William Morrissey | 3032 | 121 | 22 | Common | 3.9908% | 0.7256% | 18.1818% | William Mathews | 2264 | 91 | 2 | Common | 4.0194% | 0.0883% | 2.1978% | Thomas Nurre | 3000 | 121 | 6 | Common | 4.0333% | 0.2000% | 4.9587% | Arthur Ney Jr. | 3710 | 150 | 17 | Common | 4.0431% | 0.4582% | 11.3333% | Ann Marie Tracey | 3141 | 127 | 13 | Common | 4.0433% | 0.4139% | 10.2362% | Robert Kraft | 3138 | 127 | 7 | Common | 4.0472% | 0.2231% | 5.5118% | Richard Niehaus | 3353 | 137 | 16 | Common | 4.0859% | 0.4772% | 11.6788% | John O'Connor | 2969 | 129 | 12 | Common | 4.3449% | 0.4042% | 9.3023% | Norbert Nadel | 2959 | 131 | 20 | Common | 4.4272% | 0.6759% | 15.2672% | Robert Ruehlman | 3205 | 145 | 18 | Common | 4.5242% | 0.5616% | 12.4138% | Fred Cartolano | 3073 | 157 | 9 | Common | 5.1090% | 0.2929% | 5.7325% | J. Howard Sundermann Jr. | 955 | 60 | 10 | Common | 6.2827% | 1.0471% | 16.6667% |
We can also rank the judges based on the percentage of cases reversed when an appeal occurred. Table 2.3 shows this ranking. Judge Mark Painter had a low percentage of appealed cases but about 56% of those cases were reversed. Again Judge Grady had zero cases reversed when these were appealed.
Table 2.3 Judge | Disposed | Appealed | Reversed | Court | The Percentage of cases that were appealed | The Percentage of cases that were reversed | The Percentage of Cases Appealed that were Reversed | Karla Grady | 5253 | 6 | 0 | Muni | 0.11% | 0.00% | 0.00% | Deidra Hair | 2532 | 5 | 0 | Muni | 0.20% | 0.00% | 0.00% | William Mathews | 2264 | 91 | 2 | Common | 4.02% | 0.09% | 2.20% | Thomas Nurre | 3000 | 121 | 6 | Common | 4.03% | 0.20% | 4.96% | Robert Kraft | 3138 | 127 | 7 | Common | 4.05% | 0.22% | 5.51% | Fred Cartolano | 3073 | 157 | 9 | Common | 5.11% | 0.29% | 5.73% | Thomas Crush | 3372 | 89 | 6 | Common | 2.64% | 0.18% | 6.74% | Ralph Winkler | 3089 | 88 | 6 | Common | 2.85% | 0.19% | 6.82% | Mark Schweikert | 5403 | 55 | 4 | Muni | 1.02% | 0.07% | 7.27% | Beth Mattingly | 2971 | 13 | 1 | Muni | 0.44% | 0.03% | 7.69% | Mike Allen | 6149 | 43 | 4 | Muni | 0.70% | 0.07% | 9.30% | John O'Connor | 2969 | 129 | 12 | Common | 4.34% | 0.40% | 9.30% | Ronald Panioto | 12970 | 32 | 3 | Domestic | 0.25% | 0.02% | 9.38% | Ann Marie Tracey | 3141 | 127 | 13 | Common | 4.04% | 0.41% | 10.24% | Arthur Ney Jr. | 3710 | 150 | 17 | Common | 4.04% | 0.46% | 11.33% | David Davis | 7736 | 43 | 5 | Muni | 0.56% | 0.06% | 11.63% | Richard Niehaus | 3353 | 137 | 16 | Common | 4.09% | 0.48% | 11.68% | Timothy Hogan | 4683 | 67 | 8 | Muni | 1.43% | 0.17% | 11.94% | Robert Ruehlman | 3205 | 145 | 18 | Common | 4.52% | 0.56% | 12.41% | Timothy Black | 7954 | 41 | 6 | Muni | 0.52% | 0.08% | 14.63% | Norbert Nadel | 2959 | 131 | 20 | Common | 4.43% | 0.68% | 15.27% | Penelope Cunningham | 2308 | 13 | 2 | Domestic | 0.56% | 0.09% | 15.38% | James Patrick Kenney | 2798 | 6 | 1 | Muni | 0.21% | 0.04% | 16.67% | J. Howard Sundermann Jr. | 955 | 60 | 10 | Common | 6.28% | 1.05% | 16.67% | Dennis Helmick | 7712 | 29 | 5 | Muni | 0.38% | 0.06% | 17.24% | Nadine Allen | 7812 | 34 | 6 | Muni | 0.44% | 0.08% | 17.65% | David Stockdale | 5371 | 22 | 4 | Muni | 0.41% | 0.07% | 18.18% | William Morrissey | 3032 | 121 | 22 | Common | 3.99% | 0.73% | 18.18% | William Mallory | 8799 | 48 | 9 | Muni | 0.55% | 0.10% | 18.75% | Patrick Dinkelacker | 7259 | 63 | 12 | Domestic | 0.87% | 0.17% | 19.05% | Melba Marsh | 8219 | 34 | 7 | Muni | 0.41% | 0.09% | 20.59% | John A. West | 2797 | 13 | 3 | Muni | 0.46% | 0.11% | 23.08% | Deborah Gaines | 8277 | 38 | 9 | Domestic | 0.46% | 0.11% | 23.68% | Jack Rosen | 7790 | 41 | 13 | Muni | 0.53% | 0.17% | 31.71% | Joseph Luebbers | 5178 | 25 | 8 | Muni | 0.48% | 0.15% | 32.00% | Albert Mestemaker | 4975 | 28 | 9 | Muni | 0.56% | 0.18% | 32.14% | Leslie Isaiah Gaines | 5282 | 35 | 13 | Muni | 0.66% | 0.25% | 37.14% | Mark Painter | 2239 | 9 | 5 | Muni | 0.40% | 0.22% | 55.56% |

Because this county has such a low appeal rate it is difficult to rank the judges based on the percentage of appealed cases. We must also look at the percentage of reversed cases when appeals occur. The following criteria can be used in grading the judges in order to create conclusions based on the data provided. Table 2.4 and 2.5 show the grade scales used to apply a corresponding grad to each judge.
Table 2.4: Grade Scale based on percentage of disposed cases that were appealed (1st letter of rank) Class | Class Limits | Grade | 1 | 0.0000-0.0123 | A | 2 | 0.0124-0.0247 | B | 3 | 0.0248-0.0371 | C | 4 | 0.0372-0.0495 | D | 5 | >0.0496 | F |

Table 2.5: Grade Scale based on percentage of disposed cases that were both appealed and reversed (2nd letter of rank) Class | Class Limits | Grade | 1 | 0.00-0.11 | A | 2 | 0.12-0.23 | B | 3 | 0.24-0.35 | C | 4 | 0.36-0.47 | D | 5 | 0.48-0.59 | F |

The following are the final ranks for the judges based on the provided data and aforementioned criteria. Judge | Final Rank | Karla Grady | AA | Deidra Hair | AA | Ronald Panioto | AA | Beth Mattingly | AA | Mike Allen | AA | Mark Schweikert | AA | James Patrick Kenney | AB | Dennis Helmick | AB | David Stockdale | AB | Melba Marsh | AB | Nadine Allen | AB | John A. West | AB | Timothy Black | AB | William Mallory | AB | David Davis | AB | Penelope Cunningham | AB | Patrick Dinkelacker | AB | Deborah Gaines | AC | Joseph Luebbers | AC | Jack Rosen | AC | Albert Mestemaker | AC | Leslie Isaiah Gaines | AD | Mark Painter | AF | Timothy Hogan | BB | Thomas Crush | CA | Ralph Winkler | CA | William Mathews | DA | Thomas Nurre | DA | Arthur Ney Jr. | DA | Ann Marie Tracey | DA | Robert Kraft | DA | John O'Connor | DA | William Morrissey | DB | Richard Niehaus | DB | Norbert Nadel | DB | Robert Ruehlman | DB | Fred Cartolano | FA | J. Howard Sundermann Jr. | FB |
Summary of Rank
6 out of the 38 judges received a rank of AA – this rank indicates a low percentage of cases appealed and a low percentage of cases reversed as a result of an appeal.
2 out of the 38 judges received an F rank when looking at their percentage of cases appealed but their rank in cases reversed as a result of an appeal was A, B respectively.
10 out of the 38 judges received a D in cases appealed but also received wither an A or B in cases reversed.
Most judges received a favorable rank.

Summary of Rank
6 out of the 38 judges received a rank of AA – this rank indicates a low percentage of cases appealed and a low percentage of cases reversed as a result of an appeal.
2 out of the 38 judges received an F rank when looking at their percentage of cases appealed but their rank in cases reversed as a result of an appeal was A, B respectively.
10 out of the 38 judges received a D in cases appealed but also received wither an A or B in cases reversed.
Most judges received a favorable rank.

As previously listed we can see that a great deal of judges rank A in percent of disposed cases being appealed. 21 out of 38 judges ranked A-C in percentage of cases that were both appealed and reversed. Meaning that only a low percentage of these cases were appealed and reversed. It is also fair to say that 10 out of the 38 judges received a rank of D in cases appealed, however they received a rank of A or B in cases appealed and reversed, meaning that although their percentage of cases appealed was relatively high, the percentage of cases appealed was low. Finally we can conclude that most judges in Hamilton County are doing a good job.