Because the Y2K transition was both complex and important to the GCP, we
have conducted a large number of exploratory analyses, some of which are
quite interesting even though they cannot be used as evidence in
support of any Formal Predictions.
In addition to the material in this survey of explorations,
various other subsidiary analyses have been performed to examine the
data taken around the time of the New Year transition. These are
available for study in the First Results
page and via other links.
Formal prediction, RDN, analysis by George deBeaumont
Based on the significant results shown during the New Year
transition 1998 to 1999, a similar prediction was made
that the Y2K data would show unusual structure
around midnight, specifically in the period midnight
± 5 minutes, across all eggs
and all time zones. The prediction specified that the raw
secondbysecond data would be used, and that the measure would be the
composite Chisquare
representing the total deviation from expectation
across all data for the 10minute period.
One of the assumptions made for the sake of hypothesis generation for
the GCP is that the effects are spatially nonlocal, and under this
assumption, each egg is affected by cotemporaneous events, no matter
where they take place on the earth. Thus, at midnight in any given time
zone, we hypothesize that the effects of the conscious engagement of everyone
celebrating there will be felt by all eggs in the GCP network. An hour
later, when the celebration reaches the next time zone, there will again
be a global effect, impinging on all of the GCP recording devices.
The following composite figure for 10 timezones and 22 eggs
was constructed on a slightly different hypothesis, using data only from
timezones where one or more eggs are located. It uses about
onefourth of the intended data, because not all eggs had reported when
it was completed, but primarily because it excludes data corresponding
to the celebration period for all timezones which did not have an egg.
Synchronized deviation of Chisquare: 22 eggs, 10 timezones, GdB
The figure does not show a consistent positive trend, so that
for this subset of the data
we would have to conclude that the formal prediction of a deviation in
the 10 minutes surrounding midnight is not supported.
However, the nonlocality assumption requires that all eggs and all
timezones be used in the analysis, and on March 10, 2000, we
were able to construct the complete analysis.
Synchronized Deviation: 21 eggs, 10 timezones, RDN
First, to check that the
computations would produce approximately the same result, the
data from the same 10 timezones (actually 21 eggs instead of 22; I had
problems dealing with missing data in one case)
used by George deBeaumont were synchronized and plotted.
The resulting cumulative deviation trace is roughly similar in form
and the statistical outcome is virtually the same, with
Chisquare = 579.93 on 600 df, p = 0.704.
The intended analysis for this prediction requires the use of data from
all eggs and all timezones. Data are available from 27 eggs across the
24hour period of celebration around the world. Following George's
precedent for the JAM analysis, all 36 zones with integer or halfhour
differences from GMT were used for the following figure. In contrast to
the 22 egg, 10 timezone analysis, the deviation is positive, with a
Chisquare of 622.251 on 600 degrees of freedom, with an associated
pvalue of 0.257. This analysis is considered formal, but it has not
yet been independently crosschecked.
Independent prediction, Smoothed Variance, Etc.
Dean Radin postulated
that an increased coherence will be present in the data, generated in
response to the coherent interactions of large numbers of people
celebrating the Y2K transition together. This conception leads to a
prediction that the spread, or variance of the REG data should be
decreased around the moment of greatest engagement. The obvious
prediction is for that moment to be just at midnight, with a buildup
before and some lingering period of continuing celebration after.
The general
analysis procedure uses a measure of the variance across all eggs,
averaged across time zones, and smoothed with a sliding window,
typically 5 minutes wide.
The details of the method are explained in a
description of the approach Dean felt was
most suitable (Jan 23). I have tried some variations on this general
approach, which, in an exploratory mode, simply looks for signs of
structure in the data correlated
with the timing of the Y2K celebrations. In practice, an exploration
sweeps across the data compounded from all the midnights in different
timezones. The main tools for such exploration are graphical
visualization procedures, and if there is something unusual about
the data at the Y2K transition, it may be revealed in a variety of ways.
Except for prespecified analyses, such as Dean's original prediction of
a reduction in variance due to coherent engagement, these analyses are
not intended for inclusion in the formal database of GCP predictions.
Ed May and James Spottiswoode have provided
independent oversight and crosschecks.
When their analyses are available they will be added to this survey.
Dean's analysis results in a graph of the average deviation of normalized,
superposed, epoch variances.
The figure speaks for itself, strongly suggesting that
something special did occur in the GCP data around midnight. The detailed
description
of the steps in Dean's original analysis is interesting and informative.
The combined deviation drops precipitously as midnight approaches, and
reaches its extreme minimum at three seconds before midnight, the
moment of transition.
Other explorations using a related kurtosis
measure (X = e^kurt)
yielded similar results, buttressed by an extensive permutation analysis
and application of the procedures to data from 1, 2, and 15 days
after the Y2K transition.
The following two figures display these results, but note, due to a
computation error, the yaxis scale is incorrect and exaggerates the
significance; the actual maximum Z is on the order of 3.5, and the odds
in the second figure have a maximum of about 10e4 or 10e5, not 10e11.
Zscore for Kurtosis Measure, GCP Data at Midnight, Y2K and Controls
Log Odds Against Chance for Kurtosis Measure, Y2K and Controls
The kurtosis method was applied to the data from the previous
year, for comparison. These data show a somewhat similar structure to
that of the Y2K transition, but the deviation at midnight is somewhat
weaker, and there are competing minima elsewhere.
Zscore, Kurtosis measure, GCP Data, New Years, 1998
Confirmatory Explorations, RDN
The figures representing Dean Radin's analyses
certainly look as if something is going on around
midnight. To gain perspective, I performed several analyses of a
generally similar nature, focusing on the question whether the New
Year's midnight seemed to be correlated with "special" features in the EGG
data. I could not duplicate Dean's analysis exactly (probably
because he used a slightly less complete dataset), but by trying a
variety of analytic modes, found an
impressive array of indicators that parallel his finding and confirm an unusual
feature or tendency just at midnight. The situation is far more complicated
than is obvious, however. Most of these analyses are sensitive to small
changes in the parameters and such factors as the inclusiveness of the
dataset. Although this may suggest that the indicators are artifactual
and selectively chosen, I think there are far too many and that they are
too precisely aligned with the nominal Y2K "target" to be ignored.
Fortunately, the data are available for downloading by any interested
analyst. They bear examination.
Smoothed Variance, 27 eggs, 24 and 36 timezones
This figure shows midnight plus and minus 15 minutes, with data from
27 eggs and 24 timezones. It is a simpler and more direct
implementation of the notion that variability of the data may diminish
near midnight. The figure plots the mean across timezones of the
variance taken across the 27 eggs for
each second, smoothed with a 300second window. This particular result
looks like a striking confirmation of the hypothesis,
but if the scale is expanded to include ±30 minutes,
another, larger spike appears at 18 minutes after midnight.
Furthermore, if the
number of timezones is increased to 36 so as to include the several halfhour
offset timezones, the picture changes radically. There is no spike at midnight,
but instead, a decreasing trend beginning about 5 minutes before and
ending about 2 minutes after midnight.
Note that this behavior of the variance is entirely consistent with Dean's
prediction, even though it does not maximize at midnight.
Median Squared Deviation, 27 eggs, 24 and 36 timezones
Another perspective plots changes in the deviation of the mean
trial value across eggs over the time surrounding the Y2K transition.
The cumulative sum of the median of the squared
deviation of the mean from its empirical expectation is plotted,
revealing a striking spike at midnight.
Interpreted literally, this suggests a brief but very sharp increase in
the absolute deviations of trial outcomes just at the moment of greatest
engagement in the New Year's celebration.
Notably, this spike is present with little change in its prominence in
both the 24timezone and the 36timezone datasets, shown in the
following two figures. A permutation analysis of the 36zone case
shows that the maximum
deviation is not extremely rare, with a greater value appearing
somewhere in 90.3% of the permuted datasets. The placement
of the spike so close to midnight (it maximizes at 24 seconds after)
is, however, quite
unlikely; a 4000permutation analysis yields a pvalue of 0.022
of a spike occuring this close or closer to midnight.
The combined probability of a
spike this large and this close is p = 0.020, suggesting that we might
expect to find such impressive structure merely by chance only
twice in 100 repetitions of the Y2K experiment.
The corresponding numbers for the 24zone dataset are similar, yielding a
combined pvalue of 0.017.
A prediction was made that the high (red curve)and low (blue curve)
population timezones would
show a difference in the cumulative deviations, based on such a finding
last year. The following two figures show this split for 27 eggs across
24 and 36 timezones, respectively.
There is a substantial difference in both cases, but
interpretation is difficult because the direction of the difference is
opposite for 24 and 36 zones,
with the 24 zone dataset showing the predicted positive
difference (green curve), whereas the results for the 36 zone dataset
are opposite to the predicted direction. The difference is significant
in the 24 zone case (Chisquare = 663.29, df = 200, p = 0.037), but is
not significant for the 36 zone dataset (Chisqare = 577.22, df = 600,
p = 0.741).
In parallel with the main prediction, the 36 zone results are used for
the formal results compilation.
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