If states of mind and emotion within great numbers of people
affect the GCP network, we may conjecture that the rhythms
of the day might have impose some structure on the data.
The thought is that an indirect effect might be generated by
way of the changes in consciousness related to daily
activities. The effect would be subtle but might be detected
in the form of a correlation between the two independent
measures of event-linked effects. The netvar and covar
measures do show a similar pattern of response to the
events, on average, and we can hypothesize that this
tendency to track might also be found in responses to daily
activity variations. The following is a description of Peter
Bancel's test of this notion.
I look at the netvar/covar correlation for the
average day.
I calculate the average netvar and covar for each minute of
the day over all days in the database.
The assumption is that there is something regular about
people's acitvity during a 24 hr period and this should be a
weak signal in the netvar and covar. If the 2 stats are
picking this up, then the "average" days should have a small
correlation between these stats.
This is a correlation on two 1440 element vectors (working
with minute data).
It is not significant.
However, in net/cov correlations on the event data we
learned there are net/cov correlations on the timescale of
1-2 hours. We see this but blocking or doing moving averages
on that timescale. The event results give correlation
z-scores around 2.
If I do this for the average daily net and cov, I DO find a
positive correlation of about Z = 1.5.
Coincidence?
I can check by doing the following:
If the correlation is tied to the day cycle it will wash out
if I average "days" which are incommensurate with the real
24-hr day. Easiest and most efficient way to do this is to
take "day" lengths very close to 24-hrs. This gives maximal
smearing of any signal locked to the 24-hr cycle. So I redo
the calc with "days" of lenth 1430 to 1450 minutes. Only the
"day" with 1440 minutes locks onto the 24-hr cycle, thus
testing for a correltaion signal. Here's a quick plot which
I hope is self-explanatory:
The peak is bang on the 1440 minute "day". Stats are weak,
but this
is really intriguing and may bolster other long-term stuff
we have.
Note that a sidereal day is at about -4 and appears to show
no effect.
The peak is bang on the 1440 minute "day". Stats are weak,
but this is really intriguing and may bolster other
long-term stuff we have. Note that a sidereal day is at
about -4 and appears to show no effect.