Definition and Correct Interpretation
A confidence interval is a range of values estimated from sample data within which the true population parameter is likely to fall. A 95% confidence interval means that if you repeated the sampling procedure 100 times, approximately 95 of those intervals would contain the true value.
Common Misconceptions
The interpretation that "there is a 95% probability the true value lies within this interval" is technically incorrect. The true value is a fixed constant; it is the interval that varies across samples. In practice, however, treating it as a range where the true value likely resides is acceptable for most applications.
Relationship with Sample Size
Larger sample sizes produce narrower confidence intervals, improving estimation precision. Quadrupling the sample size roughly halves the interval width. Conversely, estimates from small samples carry wide intervals and substantial uncertainty.
Uncertainty in Rankings
The source data behind world rankings comes from surveys with varying sample sizes and methodologies across countries. Rankings displayed by MyRank carry inherent uncertainty. Understanding confidence intervals helps you avoid overinterpreting small differences in rank and instead view results with appropriate nuance.