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Resident Students Aged 5+ by Language, Education, and Sex (Census 2020)

Note: These reports were automatically generated via AI. Conclusions drawn may be in-accurate.

About this report

Author:
Citizen Insights AI
Reporting agency:
Singapore Department of Statistics
Last updated:
December 14, 2024
Data Source:
data.gov.sg

What this data tells us

Key Insight

The data reveals the language distribution among resident students aged 5 and over in Singapore, categorized by their level of education and sex.  English is the most prevalent language spoken at home, followed by Mandarin and Malay.  A notable trend is a higher proportion of females in higher education levels, particularly at the university level across most language groups.  There are also noticeable discrepancies in the representation of males and females within specific language and education categories, indicating potential areas for further investigation into educational equity and language proficiency patterns.

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Small Interesting Points of Note

The dataset includes several instances where numerical values are represented as '-' denoting missing values. This lack of data limits the conclusions that can be fully drawn from the complete dataset.

The number of students speaking 'English Only' is significantly lower than those speaking 'English & Mandarin,' highlighting the prevalence of bilingualism in Singapore.

While English is predominantly spoken at home, there's a significant number of students whose primary language is Mandarin, demonstrating a strong presence of Mandarin speakers within the student population.

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Methodology

  • Analyzed the provided dataset focusing on the 'Total_Total', 'Total_Males', and 'Total_Females' columns to understand overall language prevalence.
  • Compared the numbers of males and females across different language categories and education levels to identify gender disparities.
  • Calculated the proportions of males and females within each language group at each educational level to assess the relative distribution.
  • Identified and noted instances of missing values represented by '-' in the dataset, acknowledging their impact on the completeness of the analysis.

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Footnotes

1Note: Some headers in the original dataset contained superscript numbers (e.g., "Mandarin1/"). The superscript numbers were ignored in the analysis.  The data presented reflects only the main language category.