Sampling Error
A statistical error to which an analyst exposes a model simply because he or she is working with sample data rather than population or census data. Using sample data presents the risk that results found in an analysis do not represent the results that would be obtained from using data involving the entire population from which the sample was derived. Investopedia Says:
The use of a sample relative to an entire population is often necessary for practical and/or monetary reasons. Although there are likely to be some differences between sample analysis results and population analysis results, the degree to which these can differ is not expected to be substantial.
Methods of reducing sampling error include increasing the sample size and ensuring that the sample adequately represents the entire population. Related Terms:
Absolute Frequency
Coefficient Of Variation - CV
Heteroskedastic
Homoskedastic
Non-Sampling Error
Regression
Sample
Sample Selection Bias
Statistics
Variance |