We present an instructional approach to teaching causal inference using Bayesian networks and "do"-Calculus, which requires less prerequisite knowledge of statistics than existing approaches and can be consistently implemented in beginner to advanced levels courses. Moreover, this approach aims to address the central question in causal…

Radical behaviorism considers private events to be a part of ongoing observable behavior and to share the properties of public events. Although private events cannot be measured directly, their roles in overt action can be inferred from mathematical models that relate private responses to external stimuli and reinforcers according to the same…

Observers given brief exposures of pairs of colored bars and asked to report both the color and the orientation of each bar showed evidence of stochastic independence between reports of the 4 features (2 colors and 2 orientations). The authors also found virtually perfect stochastic independence between reports of colors and directions of motion…