Case Study Of MBA Schools In Asia Pacific After My MBA

8case Study Mba Schools In Asia Pacificafter Receiving My MBA I Was

Analyze the statistical data collected from twenty-six business schools in the Asia-Pacific region to answer specific questions related to enrollment, faculty, tuition, student demographics, test requirements, salaries, and other relevant variables. Use Excel or similar tools to compute measures such as mean, median, standard deviation, minimum, maximum, and quartiles for quantitative data. Discuss differences in tuition fees, analyze percentage distributions of foreign students and test requirements, and evaluate salary data, including implications of skewness and application of the empirical rule.

Paper For Above instruction

Following the reception of my MBA and subsequent employment at Bloomberg Business in its media division, I was tasked with analyzing data on business schools across the Asia-Pacific region. This analysis aimed to provide comprehensive statistical insights into various aspects of these institutions, including enrollment figures, student-faculty ratios, tuition fees, student demographics, standardized test requirements, and starting salaries. The data set comprised 26 schools, with variables classified as either quantitative or qualitative. Quantitative data included enrollment numbers, students per faculty, tuition fees, ages, percentage of foreign students, and starting salaries; qualitative data encompassed school names, GMAT and English test requirements, and work experience mandates.

The quantitative data were further categorized into discrete and continuous variables. Discrete variables such as full-time enrollment and student age represented countable data points, while continuous variables like tuition fees and salaries expressed measurable quantities that could take any value within a range. Using Excel, I calculated key statistical measures for each continuous variable, including the mean, median, standard deviation, minimum, maximum, and three quartiles, to understand central tendencies and data dispersion.

The analysis revealed that the average full-time enrollment across these schools was 165 students, with a median of 126. This discrepancy indicates a skewed distribution where some institutions, like the Indian Institute of Management in Calcutta with 463 students, have significantly higher enrollments compared to schools like Macquarie Graduate School of Management in Sydney, with only 12 students. The students per faculty ratio averaged 8.48, suggesting a favorable student-to-teacher ratio that enhances individual attention and individualized instruction. The age data indicated an average student age of approximately 28.36 years, with most students ranging around 29 years old, pointing toward a relatively mature student body.

Student demographic analysis showed that the mean percentage of foreign students was 28.08%, with some schools like the Asian Institute of Management in Bangkok having up to 90%. Conversely, several institutions, including Indian management schools, had almost no foreign students, with percentages at 0%, 1%, or near zero. This variation reflects differing international attractiveness and regional diversity among these schools.

In terms of standardized testing, just over half (56%) of the schools required the GMAT, while a smaller proportion (32%) mandated an English language test. A significant majority, 76%, required prior work experience from applicants, underlining the emphasis on professional background in admissions. The salary data, with a mean of approximately $37,392 and median of $41,400, showed a negative skew, indicating some graduates earned substantially lower salaries. The minimum starting salary was $7,000, and the maximum reached $87,000, with notable discrepancies between schools requiring work experience and English tests and those that did not.

Tuition fee analysis highlighted a significant difference between local and foreign tuition costs. The mean foreign tuition was approximately $16,582, whereas local tuition averaged around $12,375, a difference of roughly $4,207. A t-test confirmed this difference was statistically significant, implying that international students face higher financial barriers. Considering the salary data, schools that did not require work experience had a mean starting salary of about $24,583, whereas those requiring work experience had higher average starting salaries of approximately $41,305, suggesting that work experience may correlate with higher initial earnings.

Further statistical evaluation involved assessing data skewness, which was positive at 0.223, indicating a slight right-tailed distribution with some high salary outliers. The spread of salary data was quite broad, with a standard deviation of about $23,459. Applying the empirical rule, approximately 68% of salaries should fall within one standard deviation of the mean (between $13,833 and $60,751), and 95% should be within two standard deviations (from -$9,627 to $84,211). The actual data did not follow the empirical rule exactly but approximated these ranges, indicating some deviations, likely caused by outliers at both ends.

In conclusion, this analysis provided a comprehensive statistical portrait of MBA programs in Asia-Pacific, highlighting significant variability across institutions in terms of enrollment, international diversity, tuition fees, and graduate salaries. The findings emphasize the importance of considering these factors when choosing a program and suggest that students can expect a relatively small chance of acceptance into smaller schools but with opportunities for personalized instruction. Additionally, salary and tuition data inform prospective applicants about the potential return on investment and financial commitments needed for these programs. This analysis supports data-driven decision-making for students, educators, and policymakers involved in higher education planning in the Asia-Pacific region.

References

  • Black, K. (2017). Business Statistics: For Contemporary Decision Making (9th ed.). Wiley.
  • University of Phoenix. (2017). Case Study: MBA Schools in Asia-Pacific Data Set [Multimedia]. Retrieved from https://ecampus.phoenix.edu
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