Comoros vs Grenada: Statistical performance indicators (SPI): Pillar 5 data
Statistical performance indicators (SPI): Pillar 5 data over time
- Comoros
- Grenada
How they compare
Comoros currently reports 40 scale 0-100 against 40 scale 0-100 in Grenada, a difference of 0 scale 0-100.
The two have swapped places 2 times across 9 shared years of data; in 2016 it was Grenada ahead.
Comoros ranks 162nd and Grenada ranks 162nd of 192 countries.
Comoros has averaged higher in every one of the 2 decades both report.
Head to head by decade
| Decade | Comoros | Grenada | Difference | Ahead |
|---|---|---|---|---|
| 2010s | 23.75 scale 0-100 | 23.75 scale 0-100 | 0 scale 0-100 | — |
| 2020s | 38 scale 0-100 | 32 scale 0-100 | 6 scale 0-100 | Comoros |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher statistical performance indicators (spi): pillar 5 data, Comoros or Grenada?
- Comoros, at 40 scale 0-100 against 40 scale 0-100 in Grenada as of 2024.
- What is the difference in statistical performance indicators (spi): pillar 5 data between Comoros and Grenada?
- 0 scale 0-100, with Comoros ahead.
- How many years of comparable data are there for Comoros and Grenada?
- 9 years are reported by both, from 2016 to 2024.
- How do Comoros and Grenada rank globally for statistical performance indicators (spi): pillar 5 data?
- Comoros ranks 162nd and Grenada ranks 162nd of 192 countries.
- Where does this data come from?
- Statistical Performance Indicators, World Bank (WB), published as Statistical performance indicators (SPI): Pillar 5 data infrastructure score (scale 0-100). Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
The data infrastructure pillar overall score measures the hard and soft infrastructure segments, itemizing essential cross cutting requirements for an effective statistical system. The segments are: (i) legislation and governance covering the existence of laws and a functioning institutional framework for the statistical system; (ii) standards and methods addressing compliance with recognized frameworks and concepts; (iii) skills including level of skills within the statistical system and among users (statistical literacy); (iv) partnerships reflecting the need for the statistical system to be inclusive and coherent; and (v) finance mobilized both domestically and from donors.