Abstract
The objective of random sampling is to be able to draw valid statistical inferences about properties or parameters of the population from which the sample is drawn. For example, a random sample of a company’s employee medical claims drawn for auditing may have the purpose of estimating the proportion of improper allowances in the entire set of claims for a given time period. Other statistical inferences that rely on sampling include hypothesis tests about purported parameter values, prediction of future events, and selection or ranking of populations along some dimension of preferability.
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Notes
- 1.
This estimator is slightly biased because \( E\widehat{T}>T \). To substantially eliminate this bias one uses the slightly modified estimator T = {(m + 1)(n + 1)/(x + 1)} − 1.
- 2.
Wisconsin v. City of New York, 517 U.S. 1 (1996).
- 3.
Department of Commerce v. United States House of Representatives, 525 U.S. 316 (1999).
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Finkelstein, M.O., Levin, B. (2015). Sampling Issues. In: Statistics for Lawyers. Statistics for Social and Behavioral Sciences. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-5985-0_9
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DOI: https://doi.org/10.1007/978-1-4419-5985-0_9
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