There are two concepts of causes, property causation and token causation. The principle I want to discuss describes an epistemological connection between the two concepts, which I call the Connecting Principle. The rough idea is that if a token event of type Cis followed by a token event of type E, then the support of the hypothesis that the first event token caused the second increases as the strength of the property causal relation of C to E does. I demonstrate (...) the principle, illustrate its application to phylogenies, infections, and rumours, and discuss its consequence for the conceptual distinctness of causal processes from the events they connect. Although I am by no means confident that the Connecting Principle is ultimately correct, it seems to be a useful point of departure into an important aspect of the epistemology of causality. (shrink)

After clarifying the probabilistic conception of causality suggested by Good (1961-2), Suppes (1970), Cartwright (1979), and Skyrms (1980), we prove a sufficient condition for transitivity of causal chains. The bearing of these considerations on the units of selection problem in evolutionary theory and on the Newcomb paradox in decision theory is then discussed.

Although statistical techniques like regression analysis and path analysis are widely used in the biomedical, behavioral and social sciences to make causal inferences there has been surprisingly little philosophical discussion of the details of such techniques and of the conceptions of causation and explanation implicit in them. There also has been relatively little attempt to compare such techniques with various probabilistic models of causation and explanation in the philosophical literature.In this paper I explore, for reasons of space in a very (...) sketchy and schematic way, some issues in philosophy of science raised by regression analysis. One general conclusion I reach is that it is considerably less obvious than one might suppose that the philosophical theories alluded to above are plausibly viewed as reconstructions of regression techniques. (shrink)