Differences between probability and frequency judgments: The role of individual differences in working memory capacity

Most theories of probability judgment assume that judgments are made by comparing the strength of a focal hypothesis relative to the strength of alternative hypotheses. In contrast, research suggests that frequency judgments are assessed using a non-comparative process; the strength of the focal hypothesis is assessed without comparing it to the strength of alternative hypotheses. We tested this distinction between probability and frequency judgments using the alternative outcomes paradigm (Windschitl, Young, & Jenson, 2002). Assuming that judgments of probability (but not judgments of frequency) entail comparing the focal hypothesis with alternative hypotheses, we hypothesized that probability judgments would be sensitive to the distribution of the alternative hypotheses and would be negatively correlated with individual differences in working memory (WM) capacity. In contrast, frequency judgments should be unrelated to the distribution of the alternatives and uncorrelated with WM-capacity. Results supported the hypotheses.     

De Finettian Logics of Indicative Conditionals Part II: Proof Theory and Algebraic Semantics

Journal of Philosophical Logic - In Part I of this paper, we identified and compared various schemes for trivalent truth conditions for indicative conditionals, most notably the proposals by de...     

Diagnostic hypothesis generation and human judgment

Diagnostic hypothesis-generation processes are ubiquitous in human reasoning. For example, clinicians generate disease hypotheses to explain symptoms and help guide treatment, auditors generate hypotheses for identifying sources of accounting errors, and laypeople generate hypotheses to explain patterns of information (i.e., data) in the environment. The authors introduce a general model of human judgment aimed at describing how people generate hypotheses from memory and how these hypotheses serve as the basis of probability judgment and hypothesis testing. In 3 simulation studies, the authors illustrate the properties of the model, as well as its applicability to explaining several common findings in judgment and decision making, including how errors and biases in hypothesis generation can cascade into errors and biases in judgment.     

Probability,rational single-case decisions and the Monty Hall Problem

The application of probabilistic arguments to rational decisions in a single case is a contentious philosophical issue which arises in various contexts. Some authors (e.g. Horgan, Philos Pap 24:209–222, 1995; Levy, Synthese 158:139–151, 2007) affirm the normative force of probabilistic arguments in single cases while others (Baumann, Am Philos Q 42:71–79, 2005; Synthese 162:265–273, 2008) deny it. I demonstrate that both sides do not give convincing arguments for their case and propose a new account of the relationship between probabilistic reasoning and rational decisions. In particular, I elaborate a flaw in Baumann’s reductio of rational single-case decisions in a modified Monty Hall Problem.     

De Finettian Logics of Indicative Conditionals Part I: Trivalent Semantics and Validity

Journal of Philosophical Logic - This paper explores trivalent truth conditions for indicative conditionals, examining the “defective” truth table proposed by de Finetti (1936) and...     

Training working memory: Limits of transfer

In two experiments (totaling 253 adult participants), we examined the extent to which intensive working memory training led to improvements on untrained measures of cognitive ability. Although participants showed improvement on the trained task and on tasks that either shared task characteristics or stimuli, we found no evidence that training led to general improvements in working memory. Using Bayes Factor analysis, we show that the data generally support the hypothesis that working memory training was ineffective at improving general cognitive ability. This conclusion held even after controlling for a number of individual differences, including need for cognition, beliefs in the malleability of intelligence, and age.     

Judgment aggregation and the problem of tracking the truth

The aggregation of consistent individual judgments on logically interconnected propositions into a collective judgment on those propositions has recently drawn much attention. Seemingly reasonable aggregation procedures, such as propositionwise majority voting, cannot ensure an equally consistent collective conclusion. In this paper, we motivate that quite often, we do not only want to make a factually right decision, but also to correctly evaluate the reasons for that decision. In other words, we address the problem of tracking the truth. We set up a probabilistic model that generalizes the analysis of Bovens and Rabinowicz (Synthese 150: 131?C153, 2006) and use it to compare several aggregation procedures. Demanding some reasonable adequacy constraints, we demonstrate that a reasons- or premise-based aggregation procedure tracks the truth better than any other procedure. However, we also illuminate that such a procedure is not in all circumstances easy to implement, leaving actual decision-makers with a tradeoff problem.