Insights From A Data Analysis Exercise- PTDF Overseas Scholarships 2022

People migrate for many reasons. It may be for work, to join family, or to study. In Nigeria, further education is one of the main reasons for migration. This is generally due to the higher quality of education obtainable from these climes, or access to more opportunities globally. While many do this through self-funding, scholarships also serve as a major means for funding further studies abroad. Some popular scholarships enjoyed by Nigerians include Commonwealth, Master card, Chevening, PTDF, amongst others.

The PTDF overseas scholarship offered by PTDF - Petroleum Technology Development Fund, is one of the most rewarding ones out there, and it recently shortlisted over 8,800 people for interviews, eventually offering scholarships to 403 individuals for its MSc. and Ph.D. scholarships. This article evaluates publicly available data and offers some insights into the process.

Data Sources and Extraction process:

Through simple web scrapping capabilities of Microsoft Excel, data for this project was sourced from the PTDF website and other online sources. The shortlisted candidates for the interviews and eventual awardee data were extracted from the PTDF website: PTDF. Geopolitical zone distribution and population data were obtained from the internet.

Power query and power pivot capabilities were utilized in cleaning up the data and creating appropriate relationships to facilitate cross-filtering capabilities. These relationships facilitated categorization across states, geopolitical zones, program type i.e., MSc. Or PhD., and intended country of study. This model provided some interesting insights into the scholarship process.

Data model for the Project

Insights and results:

A summary report comprising of simple visualizations including pie charts, bar charts, and hierarchy charts was created using Microsoft's Power BI tool. Different indices were examined from which the following were derived.

8,869 candidates across 749 Local Government Areas (LGAs) and 36 states of the Federation, and the FCT were invited for the interviews from which 403 candidates from 282 LGAs across the 36 states and FCT were selected for the scholarship award. Of the 403 awardees, 243 applicants representing 60% of awardees were for the MSc scholarships, while the remaining 160 candidates- 40% obtained the Ph.D. scholarships.

Interview Stage Summary Board

Awards Stage Summary Board

The interview stage had 6,258 applicants representing 71% of candidates to be interviewed for the MSc Scholarships, and 2,611 applicants representing 29% of candidates for the PhD Scholarships. A breakdown of the applicants across geopolitical zones was also assessed.

Geopolitical Distribution of Interview Stage Candidates

Geopolitical Distribution of Awarded Candidates

6,123 candidates representing about 70% of interview stage applicants chose the UK as their preferred country of study with France, Germany, and Malaysia accounting for the remainder 30%. The Awarded scholarships however saw 206 awardees or 51% of scholarship awardee destinations being the UK, 21% being France, 16% for Germany, and 12% for Malaysia.

Distribution of Awardees Across Scholarship Countries

With 377 candidates, Kano State ranks number 1 as the State with the highest number of candidates at the interview stage. Anambra state with 14 awardees however had the highest number of candidates awarded scholarships. The average number of scholarship awardees per state is 11. The States with the least number of candidates at the interview stage are Taraba State and FCT with 147 candidates each. The least number of scholarships awarded to any state was 10.

Summary Tables for Data From Interviews and Awards

An analysis of the awardees based on gender showed that females made up only 31% of the total awardees for 2022. Breaking this down, 35% of MSc awardees were females while only 25% of awardees were females for the Ph.D. segment. On a country basis, females accounted for just 20% of France and Malaysian scholarship awards, 28% only for Germany, and 38% for the UK.

A deep dive showed that while there is room for improvement in terms of gender parity, future female applicants can improve their chances of securing a scholarship by applying to other study locations aside from the UK.

Gender Distribution of Awarded candidates

Conclusion:

Exercises like this are one of the ways I hone my Data Analysis skills using real-life data. I am open to discussions with like-minded individuals who appreciate data and its applications. Meanwhile, congratulations to the award winners, go make Nigeria proud!

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