samplingfeil

Samplingfeil, or sampling error, is the discrepancy between a population parameter and the corresponding statistic computed from a sample drawn from that population. It reflects the natural variation that occurs because the sample represents only a portion of the whole population. While sampling error cannot be eliminated, it decreases as the sample size increases and as the sampling method approaches a true random draw.

Causes and nature. Even with a perfectly random sample, the estimate will differ from the unknown population value because different samples yield different results. Sampling error depends on the variability of the characteristic being measured and on the size of the sample. For a mean, the standard error generally decreases with the square root of n; for a proportion, it is roughly sqrt(p(1-p)/n).

Measurement error and nonresponse bias are related but distinct sources of error; they are not samplingfeil, but they can compound total error in a study. Researchers quantify sampling error with the standard error and report confidence intervals or margins of error to express the range within which the true value is likely to lie. In complex surveys, variance estimation may require design-adjusted methods to reflect stratification, clustering, or weighting.

Reduction and best practices. To reduce samplingfeil, researchers increase sample size, use random or stratified sampling, ensure the sampling frame adequately covers the population, and apply weights to correct for unequal selection probabilities or nonresponse. Clear documentation of sampling design, response rates, and variance estimation improves the interpretability and reproducibility of results.