Probability and Causality is a critical analysis of the problem of causality in indeterministic contexts. Most philosophers who have written about probabilistic causality feel that Hume's requirement of constant conjunction should be replaced by a requirement of positive statistical relevance. After arguing that a theory of probabilistic causality is necessary to account for many causal relations, Hume's theory of probabilistic causality is analyzed. Although Hume's theory is inadequate, it does form the basis for later discussions of probabilistic causality. The first modern treatment of probabilistic causality is that of Hans Reichenbach, and it is discussed in detail since all later theories rely upon his basic intuitions. Reichenbach presented a proof that probabilistic definitions of causality were equivalent to the non-probabilistic analyses based on mark transmission. This proof is analyzed, and although it fails, several possible modifications of it are discussed. The next theory discussed is that of Patrick Suppes. It is shown that Suppes' theory is intrinsically defective, and that no minor modifications of his theory will be sufficient to solve the problems it faces. I. J. Good's quantitative theory of causation is then also shown to be defective. Although almost all theories of probabilistic causality assume that causes raise the probability of their effects, there is no real defense of that requirement. The author attempts to clear up the confusion surrounding the discussions of this requirement by showing that two related but distinct causal concepts are being confused. The related problem of Simpson's paradox is then discussed, and it is shown that all proposed solutions to it face serious philosophical problems. Salmon developed a theory of probabilistic causality which analyzes causal relations in terms of mark transmission instead of probability relations. The counterfactual aspect of mark transmission and causal interaction is closely examined. Probability and Causality concludes with an appendix in which the various interpretations of probability are discussed in reference to developing a theory of probabilistic causality.

by Shiu-hang Chan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaves [53]-[55]). / Chapter Chapter 1 --- Introduction --- p.1 / Chapter § 1.1 --- Usefulness of causality / Chapter § 1.2 --- Definitions of causality / Chapter § 1.2.1 --- An intuitive definition / Chapter § 1.2.2 --- A methematical definition / Chapter § 1.2.3 --- An operational definition / Chapter § 1.3 --- Test for causal orderings / Chapter § 1.3.1 --- The Granger test / Chapter § 1.3.2 --- The Sims test / Chapter § 1.3.3 --- The modified Sims test / Chapter § 1.4 --- Hsiao's sequential procedure / Chapter § 1.5 --- AIC criterion / Chapter § 1.5.1 --- A review of the AIC criterion / Chapter § 1.6 --- Summary / Chapter Chapter 2 --- Robust methods for fixed lag approach --- p.23 / Chapter § 2.1 --- The Granger M test / Chapter § 2.2 --- Estimation of residual scale / Chapter § 2.3 --- Other choices of p functions / Chapter § 2.4 --- Practical implementation / Chapter § 2.5 --- The design of the sampling experiments / Chapter § 2.5.1 --- The statistical model used to generate experimental data / Chapter § 2.5.2 --- The four tests and distributions of the data / Chapter § 2.5.3 --- The procedure to obtain the experimental data / Chapter § 2.5.4 --- The pre-determined lag for the tests / Chapter § 2.5.5 --- Simulation result / Chapter Chapter 3 --- Methods for finding the lag length of the models --- p.39 / Chapter §3.1 --- A robust sequential test / Chapter § 3.2 --- "Some choices of a for the AIC(α,p) criterion" / Chapter § 3.3 --- The convergence rate of AIC and AICR criteria / Chapter § 3.4 --- The simulation / Chapter § 3.4.1 --- Generate the data / Chapter § 3.4.2 --- The causality testing procedure / Chapter § 3.4.3 --- The simulation result / Chapter Chapter 4 --- The robust testing procedure in 3-variable case --- p.49 / Chapter § 4.1 --- Introduction / Chapter § 4.2 --- Definitions of causality in the presence of a third variable / Chapter § 4.2.1 --- An intuitive definition / Chapter § 4.3 --- The robust sequential test for 3-variable case

It is now common to hold that causes do not always (and perhaps never) determine their effects, and indeed theories of "probabilistic causation" abound. The basic idea of these theories is that C causes E just in case C and E both occur, and the chance of E would have been lower than it is had C not occurred. The problems with these accounts are that (i) the notion of chance remains primitive, and (ii) this account of causation does not coincide with the intuitive notion of causation as ontological support. Turning things around, I offer an analysis of chance in terms of causation, called the causal theory of chance. The chance of an event E is the degree to which it is determined by its causes. Thus chance events have full causal pedigrees, just like determined events; they are not "events from nowhere". I hold that, for stochastic as well as for deterministic processes, the actual history of a system is caused by its dynamical properties (represented by the lagrangian) and the boundary condition. A system is stochastic if (a description of) the actual history is not fully determined by maximal knowledge of these causes, i.e. it is not logically entailed by them. If chance involves partial determination, and determination is logical entailment, then there must be such a thing as partial entailment, or logical probability. To make the notion of logical probability plausible, in the face of current opposition to it, I offer a new account of logical probability which meets objections levelled at the previous accounts of Keynes and Carnap. The causal theory of chance, unlike its competitors, satisfies all of the following criteria: (i) Chance is defined for single events. (ii) Chance supervenes on the physical properties of the system in question. (iii) Chance is a probability function, i.e. a normalised measure. (iv) Knowledge of the chance of an event warrants a numerically equal degree of belief, i.e. Miller's Principle can be derived within the theory. (v) Chance is empirically accessible, within any given range of error, by measuring relative frequencies. (vi) With an additional assumption, the theory entails Reichenbach's Common Cause Principle (CCP). (vii) The theory enables us to make sense of probabilities in quantum mechanics. The assumption used to prove the CCP is that the state of a system represents complete information, so that the state of a composite system "factorises" into a logical conjunction of states for the sub-systems. To make sense of quantum mechanics, particularly the EPR experiment, we drop this assumption. In this case, the EPR criterion of reality is false. It states that if an event E is predictable, and locally caused, then it is locally predictable. This fails when maximal information about a pair of systems does not factorise, leading to a non-locality of knowledge.

The purpose of this dissertation is to advance our understanding of the intentionality and causal efficacy of mental states. More specifically, the dissertation is intended to help justify an appeal to teleological functions in the philosophy of mind. I start by examining the disjunction problem as encountered by causal/ information-theoretic accounts of intentionality. Such accounts individuate the content of mental states on the basis of their cause or the information they carry. As a result, they require a principled method of ruling out those cases in which a state is tokened in the "wrong" circumstances. Without such a method, a state's content could be massively disjunctive and error would be impossible. The dissertation then considers one type of purported solution, viz., teleological functionalism. The basic idea is that an analogy between malfunction and misrepresentation will help solve the disjunction problem by invoking a suitably naturalised notion of normativity. A state's content need not be what caused it but, rather, what should have caused it. I argue that there are two legitimate ways of understanding teleological function in this context. Selectionist theories— the current favourites— attribute functions on the basis of selection history; a thing's function is that effect or behaviour for which it has been selected. In contrast, systems-theoretic accounts attribute function on the basis of an analysis of components with regard to the workings of a whole; a thing's function is that effect or behaviour which contributes to the performance of the whole, of which that thing is a part. Upon examination, it becomes apparent that neither notion of function meets all the desiderata one might reasonably expect need to be met. This is explicable— the different notions are suited to two different, though related, explanatory projects. I argue that selectionist construals of teleological function are appropriate when, roughly, the project is that of explaining why extant features are present in the distribution and form that they are. In contrast, systems-theoretic construals of teleological function are appropriate when, roughly, the project is that of explaining how these features work. Furthermore, I argue that, from the perspective of a causal/ information-theoretic account, the normativity that is required for the project of individuating the content of mental states cannot derive solely from history. Knowing what served one's ancestors is not sufficient for knowing what one is doing now, let alone what one should be doing now. A systems-theoretic (and more specifically, a structural) teleological functional approach to the problem of intentionality, because it is importantly ahistorical, has the merit of incorporating normative considerations into the philosophy of mind without rendering the causal efficacy of intentional states unnecessarily mysterious. It also has the merit of allowing for those attributions of teleological function in biology that would not be overturned by new evolutionary information regarding selection history. Adherence solely to an etiological construal of teleological function is too restrictive in both domains. The dissertation ends with a defence of the structural approach against the charge that it is too liberal in attributing functions.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1967. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1978. / Vita. Includes bibliographical references (leaves 369-377).

Thesis (Ph. D.)--University of Wisconsin--Madison, 1972. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (B.A.)--Haverford College, Dept. of Philosophy, 2004. / Includes bibliographical references.

Many theorists take causality to be the heart of scientific explanation. If we couple this view with the idea, again common enough, that causes are something like sufficient conditions for their effects, then we have raised a difficulty for any theory of scientific explanation that admits "final" (genuine) statistical explanations, for a statistical explanation must allow that factors relevant to an event to be explained need not determine that event, but only make it probable to some degree (other than zero or one). If we do not wish to give up the possibility of genuine statistical explanations we must either (1) give up this central causal intuition in explanation, or (2) admit that causes act as something other than sufficient conditions — say in a probabilistic manner. This is, of course, little help unless we can clearly explicate the notion of a probabilistic cause, one of the tasks I have attempted to accomplish in this thesis. The general structure of this effort is in three parts. In the first chapter I generate the basic concepts underlying the notion of a probabilistic cause. In this I follow closely the development of this idea as constructed by Wesley Salmon. Within this view scientific explanation consists in the tracing of causal influence via causes as processes, and in providing the probability relations among events which are the product of causal interactions. In the second chapter I further develop the idea of causal processes by comparing this notion with the more traditional analyses of causation, the regularity and counterfactual theories. There I show how the process ontology very naturally overcomes problems in both of these views. I also note the advantages this conception of causes holds over these received views with respect to the problem of determinism. In the third and final chapter I discuss, and attempt to overcome, difficulties that are specific to the notion of a probabilistic causal process. / Arts, Faculty of / Philosophy, Department of / Graduate

The purpose of this dissertation is to advance our understanding of the intentionality and causal efficacy of mental states. More specifically, the dissertation is intended to help justify an appeal to teleological functions in the philosophy of mind. I start by examining the disjunction problem as encountered by causal/ information-theoretic accounts of intentionality. Such accounts individuate the content of mental states on the basis of their cause or the information they carry. As a result, they require a principled method of ruling out those cases in which a state is tokened in the "wrong" circumstances. Without such a method, a state's content could be massively disjunctive and error would be impossible. The dissertation then considers one type of purported solution, viz., teleological functionalism. The basic idea is that an analogy between malfunction and misrepresentation will help solve the disjunction problem by invoking a suitably naturalised notion of normativity. A state's content need not be what caused it but, rather, what should have caused it. I argue that there are two legitimate ways of understanding teleological function in this context. Selectionist theories— the current favourites— attribute functions on the basis of selection history; a thing's function is that effect or behaviour for which it has been selected. In contrast, systems-theoretic accounts attribute function on the basis of an analysis of components with regard to the workings of a whole; a thing's function is that effect or behaviour which contributes to the performance of the whole, of which that thing is a part. Upon examination, it becomes apparent that neither notion of function meets all the desiderata one might reasonably expect need to be met. This is explicable— the different notions are suited to two different, though related, explanatory projects. I argue that selectionist construals of teleological function are appropriate when, roughly, the project is that of explaining why extant features are present in the distribution and form that they are. In contrast, systems-theoretic construals of teleological function are appropriate when, roughly, the project is that of explaining how these features work. Furthermore, I argue that, from the perspective of a causal/ information-theoretic account, the normativity that is required for the project of individuating the content of mental states cannot derive solely from history. Knowing what served one's ancestors is not sufficient for knowing what one is doing now, let alone what one should be doing now. A systems-theoretic (and more specifically, a structural) teleological functional approach to the problem of intentionality, because it is importantly ahistorical, has the merit of incorporating normative considerations into the philosophy of mind without rendering the causal efficacy of intentional states unnecessarily mysterious. It also has the merit of allowing for those attributions of teleological function in biology that would not be overturned by new evolutionary information regarding selection history. Adherence solely to an etiological construal of teleological function is too restrictive in both domains. The dissertation ends with a defence of the structural approach against the charge that it is too liberal in attributing functions. / Arts, Faculty of / Philosophy, Department of / Graduate