Although the statistical tools most often used by researchers in the field of psychology over
the last 25 years are based on frequentist statistics, it is often claimed that the alternative …

In coming to understand the world—in learning concepts, acquiring language, and gras**
causal relations—our minds make inferences that appear to go far beyond the data …

Humans have the remarkable cognitive capacity to rapidly adapt to changing environments.
Central to this capacity is the ability to form high-level, abstract representations that take …

The impressive recent performance of large language models has led many to wonder to
what extent they can serve as models of general intelligence or are similar to human …

Purpose: The purpose of this article is to explain the characteristics of data (qualitative and
quantitative), secondary data, primary data, various primary data collection methods, data …

Bayesian explanations have swept through cognitive science over the past two decades,
from intuitive physics and causal learning, to perception, motor control and language. Yet …

Traditional memory research has focused on identifying separate memory systems and
exploring different stages of memory processing. This approach has been valuable for …

Cognitive science aims to reverse-engineer the mind, and many of the engineering
challenges the mind faces involve induction. The probabilistic approach to modeling …

Connectionist and dynamical systems approaches explain human thought, language and
behavior in terms of the emergent consequences of a large number of simple noncognitive …

Causal knowledge plays a crucial role in human thought, but the nature of causal
representation and inference remains a puzzle. Can human causal inference be captured by …