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Sampling Error

Definition

Sampling error refers to the discrepancy between a sample statistic and the true population parameter due to random chance. It occurs when the sample selected is not perfectly representative of the entire population.

Analogy

Imagine you have a bag of different colored marbles, and you want to know the average color distribution in the bag. However, instead of counting all the marbles, you randomly select only a few. The difference between your estimated average based on the few marbles and the actual average in the whole bag is sampling error.

Related terms

Margin of Error: Margin of error is a measure that quantifies how much sampling error can be expected in an estimate. It represents a range within which we expect our estimate to fall with a certain level of confidence.

Random Sampling: Random sampling is a method where each member of a population has an equal chance of being selected for inclusion in a sample. It helps reduce bias and ensures that samples are more representative.

Sample Size: Sample size refers to the number of individuals or observations included in a sample. A larger sample size generally reduces sampling error as it provides more accurate estimates.