Official Belgian data, explained
Low education among known 25+ by municipality in Belgium (2017)
This page maps Low education among known 25+ for one nationally comparable 2017 slice. Every figure below uses the same disclosed definition, unit, geography and source.
Education
What this indicator measures
Low education among known 25+
Indicator dossier
Data passport
- Selected reference period
- 2017
- Geography
- municipalities
- Boundary set
- Statistical sectors 2011-2017
- Measure
- Low education among known 25+
- Unit
- %
- Comparable areas
- 589
- Coverage
- 100%
Latest published slice
How to read the pattern
- Median
- 35.6%
- Unweighted area mean
- 35.4%
- Minimum
- 16.2%
- Maximum
- 55.2%
Across the valid national comparison set, the median is 35.6 %. Values extend from 16.2 to 55.2 %. This describes geographic variation; it is not a score of local quality.
Geography
Map of Belgium
- 16.2–30.3120 areas
- 30.3–34.1115 areas
- 34.1–37118 areas
- 37–40.6117 areas
- 40.6–55.2119 areas
Areas
Value distribution
| Value | Areas |
|---|---|
| 16.2–18 | 3 |
| 18–19.9 | 5 |
| 19.9–21.7 | 14 |
| 21.7–23.6 | 8 |
| 23.6–25.5 | 17 |
| 25.5–27.3 | 23 |
| 27.3–29.2 | 28 |
| 29.2–31 | 37 |
| 31–32.9 | 58 |
| 32.9–34.8 | 64 |
| 34.8–36.6 | 85 |
| 36.6–38.5 | 56 |
| 38.5–40.3 | 67 |
| 40.3–42.2 | 42 |
| 42.2–44.1 | 30 |
| 44.1–45.9 | 18 |
| 45.9–47.8 | 12 |
| 47.8–49.6 | 7 |
| 49.6–51.5 | 10 |
| 51.5–53.4 | 2 |
| 53.4–55.2 | 3 |
Explore this exact slice in the atlas Download this data as CSV
municipalities
Highest and lowest values
From 589 comparable areas, the table shows a concise descriptive high-and-low sample. Equal values do not imply equal local circumstances.
| Highest | 1 | Farciennes | 52018 | 55.2 % |
|---|---|---|---|---|
| Highest | 2 | La Calamine | 63040 | 53.9 % |
| Highest | 3 | Butgenbach | 63013 | 53.7 % |
| Highest | 4 | Bullange | 63012 | 52.6 % |
| Highest | 5 | Burg-Reuland | 63087 | 52 % |
| Highest | 6 | Amblève | 63001 | 51.3 % |
| Highest | 7 | Saint-Josse-ten-Noode | 21014 | 51.1 % |
| Highest | 8 | Dison | 63020 | 51 % |
| Highest | 9 | Châtelet | 52012 | 51 % |
| Highest | 10 | Comines-Warneton | 54010 | 50.9 % |
| Lowest | 589 | Woluwe-Saint-Pierre | 21019 | 16.2 % |
| Lowest | 588 | Lasne | 25119 | 16.4 % |
| Lowest | 587 | Sint-Martens-Latem | 44064 | 17.9 % |
| Lowest | 586 | Wezembeek-Oppem | 23103 | 18.3 % |
| Lowest | 585 | Kraainem | 23099 | 18.4 % |
| Lowest | 584 | Hove (Antwerpen) | 11021 | 18.6 % |
| Lowest | 583 | Oud-Heverlee | 24086 | 19.2 % |
| Lowest | 582 | De Pinte | 44012 | 19.6 % |
| Lowest | 581 | Chaumont-Gistoux | 25018 | 19.9 % |
| Lowest | 580 | Leuven | 24062 | 20 % |
Method and limitations
Method and limitations
No missing value is imputed. Where colour classes are used, their breaks and colours come from the catalogue; source-declared suppression remains missing.
The area mean gives every published geographic area equal weight. It is not weighted by population, exposure or area size.
Education shares use only age-25+ LOW/MIDDLE/HIGH as the known denominator. UNK is excluded from attainment shares and exposed through the known-coverage KPI. District components are summed through explicit municipality districtCode and shares are recomputed after selection.
Statbel DataLab reference year 2017.
Read the methodologySources, licence and provenance