Data reduction: sampling

Authors:
David Madigan;Martha Nason
Affiliations:
Professor of Statistics, Rutgers University, Piscataway, New Jersey;Department of Biostatistics, University of Washington, Seattle
Venue:
Handbook of data mining and knowledge discovery
Year:
2002

Citing 5
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Abstract

Beginning with the fundamental concept of simple random sampling, we describe the main uses and types of classical sampling techniques. Issues that arise include stratification, clustering, and sample size. We briefly mention how these issues are relevant and are being addressed in the context of data mining.