Key Insight

The data reveals a significant disparity in the number of Polytechnic Diploma graduates across various fields of study in Singapore in 2015. Engineering Sciences emerged as the most popular field, with a substantial lead over other disciplines. While a majority of graduates obtained their highest qualification within Singapore, a noticeable portion earned their diplomas from institutions outside the country. The gender distribution varies significantly by field, with some fields exhibiting a much higher proportion of male or female graduates.

Small Interesting Points of Note

Engineering Sciences significantly outnumbers other fields of study, suggesting a strong preference for this area among diploma graduates. The relatively small number of graduates in fields like Humanities and Social Sciences warrants further investigation into factors influencing student choice in these areas. Differences between the total number of graduates and those who obtained their qualifications in Singapore highlight the need for better understanding of international student mobility and its implications.

Methodology

• Data was obtained from the provided JSON response which contained information on the number of polytechnic diploma graduates by field of study, sex, and country of attainment of the highest qualification.
• Numerical data was parsed and analyzed to identify trends and patterns.
• Total number of graduates were compared across different fields of study.
• Gender distribution within each field of study was analyzed.
• The difference between the total graduates and those who got their highest qualification in Singapore were compared across fields of study.
• Statistical summaries (totals) were calculated for each field of study to compare their relative sizes.

Footnotes

The data set provided did not include any missing or N/A values. The analysis was based solely on the available data. Notably, there is a discrepancy in the provided data source which references data from 2015 but does not explicitly specify what year the data was collected. Additionally, numerical values such as Total_Total likely refer to thousands of individuals and this was treated as such in the analysis.