Abstract

Discusses an acceptance-rejection theory of statistical psychokinesis (PK). The theory explains observed statistical anomalies with a minimal assumption concerning the influence of an agent on a random process. Its premise is that the PK agent has the freedom to accept or reject the immanent outcome of a random binary process: if the immanent outcome is deemed unfavorable, the agent is attributed with the ability to "choose again" from the same distribution. From this it is deduced that the PK effect at the run level is maximized when the variance of the underlying random process is maximal. This acceptance-rejection theory of PK gives rise to a mathematical specification of the trial level influence that is identical to that of H. Schmidt's (1975) classical model. At the trial -level specification, and the run-level prediction, the acceptance -rejection theory conflicts with decision augmentation theory and a mean -shift model.