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Confounding Effects in Tests: A Case Study

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

Abstract

Getting proper samples is often simply not possible. Particularly when making two-sample comparisons, one frequently discovers that the two samples differ in more ways than one expects. In this case study, we consider how such confounding factors influence the outcome of statistical tests and show how, with a little luck and the right questions, we can avoid the worst mistakes.

Keywords

Wage Discrimination Marginal Association Hide Factor Partial Association Basic Business 
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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