Humans routinely make inductive generalizations about unobserved features of objects. Previous accounts of inductive reasoning often focus on inferences about a single object or feature: accounts of causal reasoning often focus on a single object with one or more unobserved features, and accounts of property induction often focus on a single…

Seven studies examined how people learn causal relationships in scenarios when the variables are temporally dependent--the states of variables are stable over time. When people intervene on X, and Y subsequently changes state compared to before the intervention, people infer that X influences Y. This strategy allows people to learn causal…

Both philosophers and psychologists have argued for the existence of distinct kinds of explanations, including teleological explanations that cite functions or goals, and mechanistic explanations that cite causal mechanisms. Theories of causation, in contrast, have generally been unitary, with dominant theories focusing either on counterfactual…

This work investigates how we process and represent event duration in on-line language comprehension. Specifically, it examines how events of different duration are processed and what type of knowledge underlies their representations. Studies 1-4 examined verbs and phrases in different contexts. They showed that durative events took longer to…

Conditionals in natural language are central to reasoning and decision making. A theoretical proposal called the Ramsey test implies the conditional probability hypothesis: that the subjective probability of a natural language conditional, P(if p then q), is the conditional subjective probability, P(q [such that] p). We report three experiments on…

Studied a way of constraining feature centrality, the causal status of features in a category through 6 experiments involving 204 undergraduate students. Results show that the causal status effect is deeply rooted in many aspects of the categorization process. Causal knowledge is shown to affect categorization by determining feature centrality.…

Proposes a coherence hypothesis that integrates both the "power" and "covariational" views of how people distinguish genuine causes from spurious ones. Results of 2 experiments involving 96 and 56 undergraduates support the hypothesis. Discusses the place of coherence within causal inference. (SLD)

We present a framework for the rational analysis of elemental causal induction--learning about the existence of a relationship between a single cause and effect--based upon causal graphical models. This framework makes precise the distinction between causal structure and causal strength: the difference between asking whether a causal relationship…

Many transformations that take place over time can only occur in one temporal direction, and adults are highly sensitive to the differences between forward and backward presentations of such events. In seven experiments using two selective-looking paradigms, 4- and 8-month-olds were shown forward and backward videotapes of events involving the…

The current studies explore causal models of heart attack and depression generated from American healers whom use distinct explanatory frameworks. Causal chains leading to two illnesses, heart attack and depression, were elicited from participant groups: registered nurses (RNs), energy healers, RN energy healers, and undergraduates. The…

The standard approach guiding research on the relationship between categories and causality views categories as reflecting causal relations in the world. We provide evidence that the opposite direction also holds: categories that have been acquired in previous learning contexts may influence subsequent causal learning. In three experiments we show…