Abstract
In this chapter, you’ll develop formal models linking cause and effect. You’ll begin with your reports, listing and, preferably, graphing your anticipated results. You’ll use these graphs to derive formal models combining deterministic and stochastic (random) elements. Probability and distribution theory help you draw the representative samples you need to assess your models.
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© 1999 Springer Science+Business Media New York
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Good, P.I. (1999). Cause and Effect. In: Resampling Methods. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-1-4757-3049-4_2
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DOI: https://doi.org/10.1007/978-1-4757-3049-4_2
Publisher Name: Birkhäuser, Boston, MA
Print ISBN: 978-1-4757-3051-7
Online ISBN: 978-1-4757-3049-4
eBook Packages: Springer Book Archive