Markov condition

Transitive reasoning distorts induction in causal chains

A probabilistic causal chain A-B-C may intuitively appear to be transitive: If A probabilistically causes B, and B probabilistically causes C, A probabilistically causes C. However, probabilistic causal relations can only guaranteed to be transitive …

Sequential diagnostic reasoning with verbal information

In sequential diagnostic reasoning, the goal is to infer the probability of a cause event from sequentially observed effects. Typically, studies investigating such tasks provide subjects with precise quantitative information regarding the strength of …

The assumption of class-conditional independence in category learning

This paper investigates the role of the assumption of class-conditional independence of object features in human classification learning. This assumption holds that object feature values are statistically independent of each other, given knowledge of …

How causal reasoning can bias empirical evidence

Theories of causal reasoning and learning often implicitly assume that the structural implications of causal models and empirical evidence are consistent. However, for probabilistic causal relations this may not be the case. We propose a causal …