⊿ Point. {R} Glossary. ◢ Keyword: S. ◥ University. {q} PhD. {tr} Training. ⚫ UK. ↂ EndNote. ☝️ Weerakkody. Sampling error. From Wikipedia, the free encyclopedia Statistical error Description[edit] Sampling Error[edit] The sampling error is the error caused by observing a sample instead of the whole population.[1] The sampling error is the difference between a sample statistic used to estimate a population parameter and the actual but unknown value of the parameter.[2] Effective Sampling[edit] In statistics, a truly random sample means selecting individuals from a population with an equivalent probability; in other words, picking individuals from a group without bias.
Failing to do this correctly will result in a sampling bias, which can dramatically increase the sample error in a systematic way. Even in a perfectly non-biased sample, the sample error will still exist due to the remaining statistical component; consider that measuring only two or three individuals and taking the average would produce a wildly varying result each time.
Sample Size Determination[edit] Bootstrapping and Standard Error[edit]