Relatively good resolution. Relative to what? :) 

Deviation requires you have something to measure against. A “source of truth”. 
So what are you measuring deviation from? 

From a system administration perspective , I want all my systems to be 
consistent. I’ll say that 

right == consistently wrong  

For many purposes. The inconsistency is what causes all manner of hair pulling 
for me as a system administrator across any meaningful fleet size. Very quickly 
you run into SSL and LDAP authentication issues. 

I do frequently run date/time checks to generate the cloud of data points , and 
I do log NTPD client and server via snmp using librenms . I’m about to dive 
into netdata graphing as well. 

I’m using a raspberry pi with gps hat for my master time source. Shortly I’ll 
be having a total of three systems (two using the same hat , one using the 
adafruit hat and being a pi2). I’ve got some interest in multiple way 
comparison and will follow this thread shortly. I’ll blog my setup and post a 
link. 

> On Dec 26, 2018, at 10:31, Chris Howard <[email protected]> wrote:
> 
> 
> 
> I see the different forms of deviation measurements and they are all 
> one-to-one comparisons.
> 
> Is there anything to be learned from doing mass data gathering?
> 
> For example, if I had a device of relatively good resolution that would let me
> timestamp the events from 100 different clocks, then questions about the
> change of the mean of the cloud of events, distance from the mean of 
> individual
> events, etc. could be obtained.
> 
> One of many things I have learned hanging around here is that some
> very very smart people have already thought of anything that
> might come to me.
> 
> It seems like, if there were a significant number of clocks involved, the mean
> of the cloud of events would help cancel out positive and negatives and 
> particularly
> remove the short term randomness ?
> 
> So, has this sort of thing been done?
> Why is everything one-to-one only?
> 
> 
> 
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