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Volume 14: Number 1: Article 5
Contributions to Variance in REG Experiments: ANOVA Models and Specialized Subsidiary Analyses
R.D. Nelson, R.G. Jahn, Y.H. Dobyns, and B.J. Dunne, Princeton Engineering
Anomalies Research, School of Engineering/Applied Science, Princeton
University, Princeton NJ 08544
Judicious application of a complementary set of sophisticated analytic
techniques to large databases from human/machine anomalous interaction
experiments can extract subtle structural features that might elude
more simplistic analyses. The combination of a multi-factor analysis
of variance (ANOVA) with various subsidiary, ad hoc approaches suggested
by the ANOVA or directly by the data, can establish an instructive hierarchy
of salient physical and subjective parameters and illuminate some of
their specific details. In this particular study, the dominant finding
is a significant correlation of anomalous effects with prescribed intentions
of the human operators, compounded of small contributions from many
individuals across many experimental conditions. The grand concatenation,
which includes all combinations of successful and unsuccessful parameters
or conditions, shows a chance probability for this correlation with
intention on the order of 10 -4. The effect apparently is
confined to non-deterministic devices; i.e., deterministic pseudorandom
sources show no overall effect. The correlation with intention for non-deterministic
sources alone has a chance probability of 10 -6. Beyond operator
intention, most of the other technical, procedural, and subjective parameters
explored show unimpressive contributions to the overall variance, with
a few notable exceptions that are clarified in the subsidiary analyses.
For example, individual differences among operators are indicated, but
there is a relatively normal distribution of effect sizes, within which
a few participants are distinguished by consistent achievement over
large databases. The temporal development of effect sizes shows a consistent
pattern of initial success that declines but then recovers. There is
essentially no evidence for a dependence of effect size on spatial or
temporal separation, supporting other indications that ordinary physical
variables have little impact on the anomalous interactions. In sum,
although the composite ANOVA models explain less than 1% of total variance,
implying very small and subtle effects, the analysis provides strong
evidence that the anomalies are statistically robust; they are not due
to chance fluctuations, but are demonstrably correlated with definable
subjective factors.
Keywords: anomalies, ANOVA, consciousness, electronic random event
generator, mind/machine interactions, models, REG, RNG
FULL TEXT:
Contributions to Variance
in REG Experiments: ANOVA Models and Specialized Subsidiary Analyses
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