Definition and Importance
Sample size is the number of observations actually collected in a statistical survey or study. When surveying an entire population is impractical, a subset is drawn to estimate overall characteristics. The size of this subset directly determines the precision and reliability of the resulting estimates.
Relationship Between Sample Size and Precision
Larger samples reduce sampling error and improve precision. The standard error is inversely proportional to the square root of the sample size, so doubling precision requires quadrupling the sample. This diminishing return means that beyond a certain point, the cost-effectiveness of adding more observations drops rapidly.
The Problem of Representativeness
Even a large sample is biased if it does not properly represent the population. Online surveys skew toward internet users, and phone surveys toward landline owners. True random sampling is ideal but difficult in practice due to non-response and unreachable segments.
World Ranking Data Samples
The World Bank and WHO data that MyRank references are based on large-scale national surveys. Developed countries typically survey tens of thousands of households, but developing countries may have smaller samples with gaps in rural coverage. Interpreting rankings requires awareness of the data's origin and scale.