Thesis (PH. D.)--University of Michigan, 1933. / Reprinted from the Transactions of the American mathematical society, vol. 46, no. 3 ... November, 1939, and vol. 54, no. 3 ... November, 1943. Bibliography: p. 424-425; 413 (second group).

Thesis - University of Michigan. / Reprinted from Sankhya: the Indian journal of statistics, vol. 8, no. 3, 1947. References: p. 233-234.

Thesis--Utrecht? / Cover title. T.-p. wanting. "Stellingen": p. [109]-111.

Inaug.-Diss.--Zürich. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Chicago, 1931. / Vita. Photolithographed. "Private edition, distributed by the University of Chicago libraries, Chicago, Illinois."

Thesis (Ph. D.)--University of Wisconsin--Madison, 1976. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Bibliography: leaf 201.

Thesis (Ph. D.)--University of Michigan, 1932. / "Reprinted from Transactions of the American Mathematical Society, vol. 36, no. 3, July, 1934 and American Journal of Mathematics, vol. LVIII, no. 4, October, 1936." eContent provider-neutral record in process. Description based on print version record.

Thesis (Ph. D.)--University of Adelaide, 2001. / Title from PDF title page (viewed on May 1, 2005). Appendix 3 (p. 836-899) is present in print edition, but lacking in this electronic edition. Includes bibliographical references (p. [900]-973) and indexes.

Two models for aggregating subjective probabilities are presented. One employs a multiplicative rule and the other a weighted average. The choice of a model is based on the type of evidence upon which the subjective probabilities were estimated. An experiment was developed to determine if people are sensitive to this difference in the type of evidence when combining subjective probabilities. Two other variables tested were the tense of the event and the experience of the subject with the use of probabilities. The type of evidence presented had an effect on the combination rule employed, whereas tense of the event did not. The naive and expert subjects approached the problems differently. An order effect due to the presentation order of the evidence within a problem was found. A momentum tendency, which may explain the order effect, was present in the expert subjects. Further research on combining subjective probabilities is indicated.

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.