Data Fact.

The dataset provides a comprehensive overview of the 2024 MBA rankings for global business schools, featuring 100 entries and 30 columns. Key columns include “School Name,” “Alumni network rank,” “Carbon footprint rank,” “Weighted salary (US$),” and “Career progress rank.” The data captures various aspects of business school performance, such as alumni network strength, environmental impact, salary outcomes, and career progression.

From the sample data, notable observations include the University of Pennsylvania: Wharton leading with a high weighted salary of $245,772 and a top FT research rank. Insead, located in France, shows a strong international presence with 96% international students and a high international board percentage of 83%. Columbia Business School, based in the US, ranks highly in career progress and has a significant salary percentage increase of 127%. SDA Bocconi School of Management in Italy excels in carbon footprint rank, indicating a strong commitment to sustainability. IESE Business School in Spain demonstrates a high level of satisfaction with an overall satisfaction score of 9.603.

Statistical insights reveal that the average salary percentage increase across schools is 117.96%, with a standard deviation of 34.68%. The mean overall satisfaction is 8.88, suggesting general contentment among students. The data highlights the diversity and internationalization of these institutions, with an average of 61.92% international students and 32.59% female faculty. This dataset is valuable for prospective students and stakeholders interested in the global standing and performance metrics of leading business schools.

Relevant inquiries

Q1. What is the relationship between the ‘Weighted salary (US$)’ and the ‘Salary percentage increase’ across different business schools?

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Data Analysis

• Weighted Salary Statistics: The average weighted salary is approximately $158,680, with a standard deviation of $36,964. The salaries range from $89,800 to $250,650.
• Salary Percentage Increase Statistics: The average salary percentage increase is 117.96%, with a standard deviation of 34.68%. The increases range from 40% to 229%.

Scatter Plot Visualization

• Visual Correlation: The scatter plot shows a positive correlation between weighted salary and salary percentage increase. As the weighted salary increases, the salary percentage increase tends to rise as well.
• Data Spread: There is a noticeable spread in the data, indicating variability in salary increases at different salary levels.

Conclusion and Insights

• Positive Correlation: There is a general trend where higher weighted salaries are associated with higher salary percentage increases across different business schools.
• Variability: Despite the positive trend, there is significant variability, suggesting that other factors may also influence salary increases.

Q2. Analyze the correlation between ‘Alumni network rank’ and ‘Career progress rank’ for business schools ranked 11 to 20. How does it compare to the top 10 schools?

Schools Ranked 11 to 20

• Correlation: The correlation between ‘Alumni network rank’ and ‘Career progress rank’ for schools ranked 11 to 20 is -0.367. This indicates a moderate negative correlation, suggesting that as the alumni network rank improves (lower rank number), the career progress rank tends to improve as well.

Top 10 Schools

• Correlation: For the top 10 schools, the correlation is -0.078. This indicates a very weak negative correlation, suggesting that there is little to no linear relationship between the alumni network rank and career progress rank in this group.

Conclusion and Insights

• Comparison: The correlation is stronger for schools ranked 11 to 20 compared to the top 10 schools. This suggests that for schools outside the top 10, a better alumni network rank is more closely associated with better career progress.
• Implication: Schools ranked 11 to 20 might benefit more from strengthening their alumni networks to enhance career progress, whereas for top 10 schools, other factors might play a more significant role in career progress.

Q3. Analyze the factors that might have contributed to the improvement in rankings for the business schools identified. Consider aspects such as changes in faculty, curriculum updates, or increased focus on internationalization.

Faculty-Related Metrics

• Lack of Data: The analysis of faculty-related metrics such as ‘Female faculty (%)’, ‘International faculty (%)’, and ‘Faculty with doctorates (%)’ did not yield any correlation data with overall rankings. This indicates a lack of available data or a negligible impact of these metrics on ranking improvements.

Curriculum-Related Metrics

• Rank Change: The curriculum-related metrics, specifically ‘ESG and net zero teaching rank’ and ‘Overall satisfaction’, showed a minimal average rank change of 0.00 with a standard deviation of 0.17. The rank changes ranged from -0.12 to 0.12, suggesting that curriculum updates might have had a minor impact on rankings.

Internationalization-Related Metrics

• Lack of Data: Similar to faculty-related metrics, the analysis of internationalization-related metrics such as ‘International students (%)’, ‘International board (%)’, ‘International mobility rank’, and ‘International course experience rank’ did not provide any correlation data with rank changes. This suggests either a lack of data or a minimal influence on ranking improvements.

Ranking Improvement Analysis

• Significant Rank Changes: The analysis identified schools with significant improvements in rankings, with a mean rank change of 12.21 from 2022 to 2023. The standard deviation was 8.05, indicating variability in rank changes among schools. The maximum rank change observed was 28.00, suggesting that some schools made substantial improvements.
• Three-Year Average Comparison: The comparison between the three-year average rank and the 2023 rank showed a mean difference of 5.30, with a standard deviation of 2.73. This indicates that schools have generally improved their rankings over the three-year period.

Conclusion and Insights

• Curriculum Updates: While curriculum updates showed minimal impact, they might still contribute to ranking improvements when combined with other factors.
• Significant Rank Improvements: Some schools have achieved notable rank improvements, suggesting that factors not captured in the available data, such as strategic initiatives or other qualitative improvements, may have played a role. Further investigation into these areas could provide additional insights.

Q4. What is the distribution of ‘International students (%)’ across different business schools, and how does it relate to the ‘International mobility rank’?

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Statistical Analysis

• Mean and Median: The average percentage of international students across business schools is approximately 61.92%, with a similar median, indicating a fairly symmetrical distribution.
• Standard Deviation: The standard deviation is 30.64, suggesting a wide range of international student percentages among different schools.
• Range: The percentage of international students varies from 0% to 100%, showing significant diversity in international representation.

Visual Representation

• Distribution Pattern: The bar chart illustrates a varied distribution of international students across numerous business schools, with many schools having high percentages (close to 100%).

Relationship with ‘International Mobility Rank’

Correlation Analysis

• Correlation Value: There is a strong negative correlation (-0.80) between the percentage of international students and the international mobility rank. This suggests that schools with higher percentages of international students tend to have better (lower) mobility ranks.

Visual Insight

• Graphical Correlation: The visualization includes a correlation annotation, reinforcing the strong inverse relationship between international student percentages and mobility rank.

Conclusion and Insights

• Diverse Representation: Business schools exhibit a wide range of international student percentages, with some schools having a fully international student body.
• Impact on Mobility Rank: A higher percentage of international students is strongly associated with a better international mobility rank, indicating that schools with more international students may offer better global mobility opportunities.

Q5. How does the ‘Carbon footprint rank’ vary among business schools located in different countries?

Query Result

Average Carbon Footprint Rank by Country

• Highest Average Rank: Denmark has the highest average carbon footprint rank at 83.0.
• Lowest Average Rank: Singapore has the lowest average carbon footprint rank at 16.0.
• Other Notable Ranks:
  • France (25.0) and Spain (26.25) have relatively low ranks.
  • Australia (67.5) and India (66.5) have higher ranks.

Visualization of Carbon Footprint Rank

• Visual Insights: The bar chart illustrates the variation in average carbon footprint ranks across countries.
• Countries with High Ranks: Denmark, Australia, and India show higher bars, indicating higher average ranks.
• Countries with Low Ranks: Singapore, Switzerland, and France have shorter bars, indicating lower average ranks.

Conclusion and Insights

• Significant Variation: There is a significant variation in the carbon footprint ranks among business schools in different countries.
• Environmental Impact Awareness: Countries with lower ranks may indicate better awareness and practices regarding environmental impact in their business schools.

Q6. Analyze the correlation between ‘Overall satisfaction **’ scores and ‘Weighted salary (US$)’ for the top 5 ranked business schools. Are higher satisfaction scores associated with higher salaries?

Correlation Result

• Correlation Value: The correlation between ‘Overall satisfaction **’ scores and ‘Weighted salary (US$)’ for the top 5 ranked business schools is -0.34.

Conclusion and Insights

• Negative Correlation: The correlation value of -0.34 indicates a weak negative relationship between satisfaction scores and salaries. This suggests that higher satisfaction scores are not necessarily associated with higher salaries among the top 5 ranked business schools.
• Implications: The weak negative correlation implies that factors other than satisfaction scores might be influencing the weighted salaries of graduates from these business schools. Further analysis could explore other variables that might impact salary outcomes.

Q7. Analyze the correlation between the percentage of ‘Female faculty (%)’ and ‘Female students (%)’ and the overall satisfaction scores of the business schools. What insights can be drawn from this relationship?

Correlation Coefficients

• Female faculty (%) and Female students (%): The correlation coefficient is 0.2246, indicating a weak positive relationship between the percentage of female faculty and female students.
• Female faculty (%) and Overall satisfaction: The correlation coefficient is -0.1947, suggesting a weak negative relationship between the percentage of female faculty and overall satisfaction scores.
• Female students (%) and Overall satisfaction: The correlation coefficient is -0.0293, indicating a very weak negative relationship between the percentage of female students and overall satisfaction scores.

Conclusion and Insights

• Weak Positive Correlation: There is a weak positive correlation between the percentage of female faculty and female students, suggesting that schools with more female faculty tend to have slightly more female students.
• Weak Negative Correlation with Satisfaction: Both the percentage of female faculty and female students show a weak negative correlation with overall satisfaction scores, indicating that higher percentages of female faculty or students do not strongly influence satisfaction scores in a positive or negative direction.

Q8. Which business schools have the highest ‘International board (%)’, and how does this relate to their ‘International course experience rank’?

Query Result

Schools with Highest ‘International Board (%)’

• Schools Identified: The schools with the highest ‘International board (%)’ are IE Business School, Ceibs, and Audencia.
• International Board Percentage: All three schools have an ‘International board (%)’ of 100%.

Relationship with ‘International Course Experience Rank’

• IE Business School: Has an ‘International course experience rank’ of 1.
• Ceibs: Has an ‘International course experience rank’ of 2.
• Audencia: Has an ‘International course experience rank’ of 3.

Visualization Insights

• Bar Chart Representation: The chart shows that while all schools have a perfect score for ‘International board (%)’, their ‘International course experience rank’ varies, with IE Business School ranking the highest in course experience.

Conclusion and Insights

• High International Board: All identified schools have a perfect international board percentage, indicating a strong global presence.
• Course Experience Variation: Despite similar board percentages, there is variation in course experience rankings, suggesting differences in international course offerings or student satisfaction.

Q9. Analyze the correlation between ‘FT research rank’ and ‘Weighted salary (US$)’ to determine if there is a linear relationship between these two variables.

Correlation Coefficient

• Correlation Coefficient Value: The correlation coefficient between ‘FT research rank’ and ‘Weighted salary (US$)’ is -0.59.

Conclusion and Insights

• Negative Correlation: The correlation coefficient of -0.59 indicates a moderate negative linear relationship between ‘FT research rank’ and ‘Weighted salary (US$)’. This suggests that as the FT research rank improves (i.e., the rank number decreases), the weighted salary tends to increase.
• Implications for Institutions: Institutions with higher research ranks might offer higher salaries, potentially attracting better faculty and researchers.

Q10. How does the ‘Value for money rank’ compare to the ‘Weighted salary (US$)’ for business schools in the US versus those in Europe?

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Data Overview

• Weighted Salary Conversion: The ‘Weighted salary (US$)’ column was successfully converted from string to integer, allowing for accurate analysis. The mean salary is approximately $166,752, with a standard deviation of $38,153.

Comparative Visualization

• US vs Europe Schools: The scatter plot illustrates the relationship between ‘Value for money rank’ and ‘Weighted salary (US$)’ for business schools in the US and Europe.
• US Schools: Represented by blue dots, US schools tend to have higher weighted salaries compared to their value for money rank.
• Europe Schools: Represented by green dots, European schools show a wider spread in value for money rank, with some schools achieving high ranks with lower salaries.

Conclusion and Insights

• Salary and Rank Correlation: US business schools generally offer higher salaries, which may not always correlate with a better value for money rank.
• Regional Differences: European schools display more variability in value for money rank, suggesting diverse offerings and potentially different market dynamics compared to US schools.