Titlebook: Causation, Prediction, and Search; Peter Spirtes,Clark Glymour,Richard Scheines Book 1993 Springer-Verlag New York, Inc. 1993 Microsoft Ac

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https://doi.org/10.1007/978-3-663-10963-1e formal apparatus we use. It may be skipped in a first reading and referred to as needed, although the reader should be warned that for good reason we occasionally use nonstandard definitions of standard notions in graph theory. We assume the reader has some background in finite mathematics and sta

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https://doi.org/10.1007/978-3-663-10963-1alyze causal influence as some sort of counterfactual relation (sometimes a counterfactual relation having to do with manipulations or interventions), and those that prefer not to talk of causation at all. We advocate no definition of causation, but in this chapter we try to make our usage systemati

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,Organisation und Geschlechterverh?ltnis,ws before the inquiry, could be the structure from which the data are obtained. There is something to be found out about the actual structure, whichever it is. It may be that we want to settle a particular hypothesis that is true in some of the possible structures and false in others, or it may be t

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Organisation und Welterschlie?ungncies among measured variables are due to unmeasured common causes. We almost always fail to measure all of the causes of variables we do measure, and we often fail to measure variables that are causes of two or more measured variables. Any examination of collections of social science data gives the

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Strukturation und Dekonstruktionate policy: Will the reduction of sources of environmental lead increase the intelligence of children in exposed regions? Will increased taxation of cigarettes decrease lung cancer? How large will these effects be? What will be the differential yield if a field is planted with one species of wheat r

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