Confounding Effects in Tests: A Case Study
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.
KeywordsWage Discrimination Marginal Association Hide Factor Partial Association Basic Business
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