The Session Analysis Machine™ (SAM™) is a sophisticated computer program designed to analyze remote-viewing data. The public release of SAM allows anyone with a computer to shift from subjective to scientific evaluations of the remote-viewing phenomenon. Now, remote viewing can be studied more objectively, and the age-old bias of rejecting remote-viewing data because the phenomenon is "not supposed to exist" can be abandoned with greater certainty. More specifically, SAM compares a data set derived from a remote-viewing session with another data set that is based on a "target." The target is what the remote-viewer is supposed to perceive during the session. Since remote-viewing data are subjective perceptions, it is difficult for some people to evaluate how well a remote viewer is perceiving a target. SAM helps this evaluative process by reducing both the remote-viewing session and the target into two numerical data sets that can be compared statistically.

But SAM does much more than work with one target. SAM can be used to conduct a thorough statistical analysis of remote-viewing data using a large variety of useful statistics simultaneously involving hundreds of targets. This includes, for example, making relative comparisons between a remote-viewing session and a host of other targets. That is, researchers may want to know how well a remote-viewing session describes a particular target by comparing how well it describes, say, hundreds of other targets. If the remote-viewing session is accurate with respect to describing its intended target, then its description of other quite different targets should be much worse, and a statistical analysis of relevant data should demonstrate this conclusively. For example, if a remote viewer is supposed to describe the Eiffel Tower, then the remote-viewing data should compare favorably with a numerical data set that contains descriptions of the Eiffel Tower. Those same remote-viewing data should not do a good job describing a scene in Antarctica, or a battle in the 1800's between ships on an ocean. SAM allows a researcher to make such comparisons easily with respect to any number of targets.