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Background <p>The underrepresentation of women in statistics and data science remains a significant challenge despite growing efforts to close the gender gap. This study explores the gender gap in these fields, examines the relationship between the Times Higher Education (THE) ranking of universities and their ranking in terms of female lecturers, and proposes strategies to foster gender diversity in Southwest Nigeria.</p> Methods <p>Data on the gender and academic rank of staff members in the statistics departments of six universities in Southwest and North-central Nigeria were collected. Descriptive statistics, including frequencies, percentages, and visual representations, were used to summarize the data. To examine the relationship between university rankings (as measured by THE ranking) and the ranking of universities based on the percentage of female academic staff, Spearman’s rank correlation was employed to assess the strength and direction of the association.</p> Results <p>The findings reveal that male lecturers significantly outnumber their female counterparts, with women constituting only 15.0-37.5% of academic staff at the surveyed universities. Furthermore, female representation declines sharply in higher positions; while women occupy some entry-level positions, higher academic ranks such as Associate Professor and Professor are predominantly held by men. A Spearman rank correlation analysis between the ranking of universities based on the percentage of female academic staff and THE ranking resulted in a coefficient of 0.2 with a <i>p</i>-value of 0.704, suggesting a weak and statistically insignificant relationship.</p> Conclusion <p>The study highlights the persistent gender disparities in academic Statistics Departments and suggests that institutional ranking does not necessarily reflect gender inclusivity in academia. To bridge this gap, the study recommends strategies such as mentorship and early exposure programs, financial assistance and scholarships, representation of role models, inclusive learning environments, networking, and professional development initiatives to encourage greater female participation in statistics and data science.</p>

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The Gender Gap in Statistics and Data Science in North Central and Southwest Nigeria

  • 期刊论文

  • 发表日期：

    2025年9月29日

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  • Christianah F. Olanrewaju,
  • Abiola T. Owolabi

摘要

Background

The underrepresentation of women in statistics and data science remains a significant challenge despite growing efforts to close the gender gap. This study explores the gender gap in these fields, examines the relationship between the Times Higher Education (THE) ranking of universities and their ranking in terms of female lecturers, and proposes strategies to foster gender diversity in Southwest Nigeria.

Methods

Data on the gender and academic rank of staff members in the statistics departments of six universities in Southwest and North-central Nigeria were collected. Descriptive statistics, including frequencies, percentages, and visual representations, were used to summarize the data. To examine the relationship between university rankings (as measured by THE ranking) and the ranking of universities based on the percentage of female academic staff, Spearman’s rank correlation was employed to assess the strength and direction of the association.

Results

The findings reveal that male lecturers significantly outnumber their female counterparts, with women constituting only 15.0-37.5% of academic staff at the surveyed universities. Furthermore, female representation declines sharply in higher positions; while women occupy some entry-level positions, higher academic ranks such as Associate Professor and Professor are predominantly held by men. A Spearman rank correlation analysis between the ranking of universities based on the percentage of female academic staff and THE ranking resulted in a coefficient of 0.2 with a p-value of 0.704, suggesting a weak and statistically insignificant relationship.

Conclusion

The study highlights the persistent gender disparities in academic Statistics Departments and suggests that institutional ranking does not necessarily reflect gender inclusivity in academia. To bridge this gap, the study recommends strategies such as mentorship and early exposure programs, financial assistance and scholarships, representation of role models, inclusive learning environments, networking, and professional development initiatives to encourage greater female participation in statistics and data science.