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Sampling

  • Dean P. Foster
  • Robert A. Stine
  • Richard P. Waterman

Abstract

This class introduces the basic issues concerned with collecting information. The problem of making a valid inference about a population based on information obtained in a sample will be the main focus. For this inference to be valid, the sample needs to be representative. Though this sounds like common sense, subtle biases often creep in when sampling is done. When this is the case, the inference may be very misleading. We will discuss some of these biases and explain sampling methods designed to avoid bias.

Keywords

Simple Random Sample Return Visit Georgia Tech Survey Variable Prior Record 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Dean P. Foster
    • 1
  • Robert A. Stine
    • 1
  • Richard P. Waterman
    • 1
  1. 1.Department of Statistics, Wharton SchoolUniversity of PennsylvaniaPhiladelphiaUSA

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