Statistical performance indicators (SPI): Pillar 4 data sources score in Guinea
Guinea: Statistical performance indicators (SPI): Pillar 4 data sources score was 34.72 scale 0-100 in 2024. ▲ Rising
Statistical performance indicators (SPI): Pillar 4 data sources score in Guinea, 2015–2024
Source: Statistical Performance Indicators, World Bank (WB). Measured in scale 0-100.
Analysis
The most recent figure for statistical performance indicators (spi): pillar 4 data sources score in Guinea is 34.72 scale 0-100, measured in 2024. That is the highest value across all 10 years on record.
That represents a change of up 2.0% on the previous year and up 36.3% over ten years.
Over the whole period, statistical performance indicators (spi): pillar 4 data sources score in Guinea peaked at 34.72 scale 0-100 in 2024 and was at its lowest, 23.43 scale 0-100, in 2017.
Guinea ranks 156th of 182 countries on this measure, in the bottom quarter.
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 25.26 scale 0-100 | 23.43 scale 0-100 | 26.73 scale 0-100 | 5 |
| 2020s | 33.43 scale 0-100 | 30.1 scale 0-100 | 34.72 scale 0-100 | 5 |
Countries ranked near Guinea
More public sector data for Guinea
- Arms imports 6.00 million SIPRI trend indicator values (2024)
- Military expenditure 2.1% (2024)
- Military expenditure 562.46 million current USD (2024)
- Armed forces personnel, total 13,000 (2020)
- Armed forces personnel 0.3% (2020)
- Statistical performance indicators (SPI): Pillar 1 data use score 66.6 scale 0-100 (2024)
- Statistical performance indicators (SPI): Pillar 3 data products score 62.65 scale 0-100 (2024)
- Military expenditure 4.84 trillion current LCU (2024)
- Proportion of seats held by women in national parliaments 29.6% (2025)
- Military expenditure 12.8% (2024)
Frequently asked questions
- What is statistical performance indicators (spi): pillar 4 data sources score in Guinea?
- Statistical performance indicators (spi): pillar 4 data sources score in Guinea was 34.72 scale 0-100 in 2024, according to Statistical Performance Indicators, World Bank (WB).
- What is the highest statistical performance indicators (spi): pillar 4 data sources score recorded in Guinea?
- The highest recorded value was 34.72 scale 0-100 in 2024.
- What is the lowest statistical performance indicators (spi): pillar 4 data sources score recorded in Guinea?
- The lowest recorded value was 23.43 scale 0-100 in 2017.
- How does Guinea rank for statistical performance indicators (spi): pillar 4 data sources score?
- Guinea ranks 156th out of 182 countries with data for 2024.
- Is statistical performance indicators (spi): pillar 4 data sources score rising or falling in Guinea?
- Over the last ten years it is up 36.3%. The long-run trend across the full record is rising.
- Where does this Guinea data come from?
- The figures come from Statistical Performance Indicators, World Bank (WB), published as part of Statistical performance indicators (SPI): Pillar 4 data sources score (scale 0-100). Statizoid updates them automatically from the source API.
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About this data
The data sources overall score is a composite measure of whether countries have data available from the following sources: Censuses and surveys, administrative data, geospatial data, and private sector/citizen generated data. The data sources (input) pillar is segmented by four types of sources generated by (i) the statistical office (censuses and surveys), and sources accessed from elsewhere such as (ii) administrative data, (iii) geospatial data, and (iv) private sector data and citizen generated data. The appropriate balance between these source types will vary depending on a country's institutional setting and the maturity of its statistical system. High scores should reflect the extent to which the sources being utilized enable the necessary statistical indicators to be generated. For example, a low score on environment statistics (in the data production pillar) may reflect a lack of use of (and low score for) geospatial data (in the data sources pillar). This type of linkage is inherent in the data cycle approach and can help highlight areas for investment required if country needs are to be met.