Wittgenstein Projection: Mean Years of Schooling. Age 25+. Gender Gap in Congo
Congo: Wittgenstein Projection: Mean Years of Schooling. Age 25+. Gender Gap was 0.16 in 2100. β Volatile
Wittgenstein Projection: Mean Years of Schooling. Age 25+. Gender Gap in Congo, 2010β2100
Source: Wittgenstein Centre for Demography and Global Human Capital: http://www.oeaw.ac.at/vid/dataexplorer/.
Analysis
In 2100, wittgenstein projection: mean years of schooling. age 25+. gender gap in Congo stood at 0.16. That is the lowest value across all 19 years on record.
That represents a change of down 23.8% over ten years.
Over the whole period, wittgenstein projection: mean years of schooling. age 25+. gender gap in Congo peaked at 2.35 in 2010 and was at its lowest, 0.16, in 2100.
That places Congo 22nd out of 166 countries with data for 2100, putting it in the top quarter.
The series is highly variable year to year, so single readings are best treated with caution.
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 2.19 | 2.03 | 2.35 | 2 |
| 2020s | 1.64 | 1.52 | 1.75 | 2 |
| 2030s | 1.22 | 1.13 | 1.31 | 2 |
| 2040s | 0.905 | 0.84 | 0.97 | 2 |
| 2050s | 0.675 | 0.62 | 0.73 | 2 |
| 2060s | 0.47 | 0.43 | 0.51 | 2 |
| 2070s | 0.345 | 0.32 | 0.37 | 2 |
| 2080s | 0.26 | 0.24 | 0.28 | 2 |
| 2090s | 0.195 | 0.18 | 0.21 | 2 |
| 2100s | 0.16 | 0.16 | 0.16 | 1 |
Countries ranked near Congo
More reference data data for Congo
- Emission Totals - Indirect emissions (N2O) - Manure applied to Soils 0.0199 (2050)
- Emission Totals - Indirect emissions (N2O) - Manure left on Pasture 0.1866 (2050)
- Emission Totals - Indirect emissions (N2O) - IPCC Agriculture 0.2108 (2050)
- Emission Totals - Indirect emissions (N2O) - Crop Residues 0.0031 (2050)
- Emission Totals - Indirect emissions (N2O) - Agricultural Soils 0.2108 (2050)
- Emission Totals - Emissions (N2O) - Manure applied to Soils 0.0668 (2050)
- Emission Totals - Emissions (N2O) - Manure Management 0.0724 (2050)
- Emission Totals - Emissions (N2O) - Manure left on Pasture 0.9126 (2050)
- Emission Totals - Emissions (N2O) - IPCC Agriculture 1.08 (2050)
- Emission Totals - Emissions (N2O) - Crop Residues 0.017 (2050)
Frequently asked questions
- What is wittgenstein projection: mean years of schooling. age 25+. gender gap in Congo?
- Wittgenstein projection: mean years of schooling. age 25+. gender gap in Congo was 0.16 in 2100, according to Wittgenstein Centre for Demography and Global Human Capital: http://www.oeaw.ac.at/vid/dataexplorer/.
- What is the highest wittgenstein projection: mean years of schooling. age 25+. gender gap recorded in Congo?
- The highest recorded value was 2.35 in 2010.
- What is the lowest wittgenstein projection: mean years of schooling. age 25+. gender gap recorded in Congo?
- The lowest recorded value was 0.16 in 2100.
- How does Congo rank for wittgenstein projection: mean years of schooling. age 25+. gender gap?
- Congo ranks 22nd out of 166 countries with data for 2100.
- Is wittgenstein projection: mean years of schooling. age 25+. gender gap rising or falling in Congo?
- Over the last ten years it is down 23.8%. The long-run trend across the full record is volatile.
- Where does this Congo data come from?
- The figures come from Wittgenstein Centre for Demography and Global Human Capital: http://www.oeaw.ac.at/vid/dataexplorer/, published as part of Wittgenstein Projection: Mean Years of Schooling. Age 25+. Gender Gap. Statizoid updates them automatically from the source API.
Download this data
CSV Β· JSON β 19 observations, free to reuse under CC BY 4.0 (World Bank Open Data).
About this data
The difference between male and female mean number of years spent in school by age group. It is calculated by subtracting the female value from the male value. Data can be negative if the mean years of schooling for females is higher than for males. Projections are based on collected census and survey data for the base year (around 2010) and the Medium Shared Socioeconomic Pathways (SSP2) projection model. The SSP2 is a middle-of-the-road scenario that combines medium fertility with medium mortality, medium migration, and the Global Education Trend (GET) education scenario. For more information and other projection models, consult the Wittgenstein Centre for Demography and Global Human Capital's website: http://www.oeaw.ac.at/vid/dataexplorer/