Explanation of my superposed epoch analysis:

Before examining the data, I presumed (1) that the turn of the millennium would produce 
a few moments of high mental coherence that would be reflected in each time zone, (2) 
that mental coherence may be reflected in physical systems as a reduction in noise or 
entropy, (3) that there may be 24 periods of reduced entropy in all eggs, centered
around the stroke of midnight, and (4) reduced entropy can be detected as a 
reduction in variance among the egg values.

To look for these reductions in entropy, I took the following steps:

a) Download all per-second raw egg data from 12/31/1999 11:30 to 01/01/2000 11:30.

b) Calculate the average absolute deviation (AAD) for these raw values, per second,
across all available eggs.  The AAD values will be our measure of "noise."

c) Create 24 one-hour blocks of AAD values, each block centered on the stroke of 
midnight in each time zone. 

d) Create a superposed epoch analysis by overlaying the 24 blocks of data.

e) Calculate the median for each of the 3600 seconds of blocked AAD data, call these
values MAAD.

f) Calculate a 5-minute moving average for the MAAD values.  Call this average
5M-MAAD.  The results are graphed in Figure 1.  The prediction is a drop in "noise" 
around the stroke of midnight, and we see that 5M-MAAD does drop.
The lowest MAAD value occurs 15 seconds after midnight.

g) Calculate a standard error for each 5M-MAAD value.  One standard error bars 
are shown in Figure 1.

h) Find the grand mean of 5M-MAAD values from Figure 1, then create standard 
normal deviates (z scores) based on this mean and the observed 5M-MAAD averages 
and standard errors determined in steps f and g.  From the resulting z-scores, 
create odds against chance for the graph in Figure 1.  These values are 
plotted in Figure 2 (one-tailed).  It is clear that something unusual occurred at the 
stroke of midnight in all of the time zones combined.

NOTE: Instead of using AAD as a measure of variance among the egg values, 
one could use standard deviation.  And instead of taking the median of 
the AAD values, one could use average.  As expected, the results vary somewhat depending 
on what statistic one chooses.  With some experimentation I found that AAD and median 
optimized the final graphs, and thus these particular stats were selected post-hoc 
to enhance the resulting spike at the stroke of midnight.  But the basic approach used
here was planned in advance of examining the data.

