Relations between premise similarity and inductive strength (original) (raw)

Four experiments investigated how people judge the plausibility of category-based arguments, focusing on the diversity effect, in which arguments with diverse premise categories are considered particularly strong. In Experiment 1 we show that priming people as to the nature of the blank property determines whether sensitivity to diversity is observed. In Experiment 2 we find that people's hypotheses about the

A considerable amount of work has focused on the processes that underlie children's inductive reasoning. For instance, numerous studies explored the role of linguistic labels, perceptual similarity, and children's beliefs in generalization of properties to novel cases. The present studies investigated an aspect of induction that has received considerably less attention in prior developmental research, namely-the effect of the statistical properties of evidence on inductive reasoning. Studies presented below were motivated by the hypothesis that induction involves an evaluation of the statistical properties available in the evidence. From this perspective, sample size, or the amount of available evidence, should influence inductive reasoning. Sample size effects were investigated in three experiments with 90 5-year-olds and 90 adults. Results indicated that children made higher rate of projections for larger than smaller samples, particularly when samples were represented by ...

A robust finding in category-based induction tasks is for positive observations to raise the willingness to generalize to other categories while negative observations lower the willingness to generalize. This pattern is referred to as monotonic generalization. Across three experiments we find systematic non-monotonicity effects, in which negative observations raise the willingness to generalize. Experiments 1 and 2 show that this effect emerges in hierarchically structured domains when a negative observation from a different category is added to a positive observation. They also demonstrate that this is related to a specific kind of shift in the reasoner's hypothesis space. Experiment 3 shows that the effect depends on the assumptions that the reasoner makes about how inductive arguments are constructed. Non-monotonic reasoning occurs when people believe the facts were put together by a helpful communicator, but monotonicity is restored when they believe the observations were sa...

Abstract Computational models of analogy have assumed that the strength of an inductive inference about the target is based directly on similarity of the analogs, and in particular on shared higher-order relations. However, in Experiment 1 we show that reducing analogical overlap by eliminating a higher-order causal relation (a preventive cause present in the source) from the target increased inductive strength even though it decreased similarity of the analogs.