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PingER non VM Measurement agent 

To World (excluding SLAC targets).

Pinger non VM measurement agent
Tickmin25th%avgmedian75th%90th%95th%maxiqrstd dev# pairs
Mar201523.312178.346239.329211.152293.499339.425379.947780.659115.153104.510107
Feb201522.689176.167241.608212.435295.448326.637362.350803.815119.281110.212112

NB. February  data is incomplete for the VM, so leave out 

To Europe
Tickmin25th%avgmedian75th%90th%95th%maxiqrstd dev# pairs
Mar2015150.996162.944175.858173.632186.939201.843204.698204.69823.99517.13114
To N. America

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To non VM Pinger MA
PingER VM measurement

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agent
Tickmin25th%avgmedian75th%90th%95th%maxiqrstd dev# pairs
Mar201523.698176.221238.352213.278294.279340.938381.412796.140118.058109.834107
Feb201522.515178.790239.368210.327301.033329.510369.066807.798122.243110.401110

To Europe

 PingER non VM Measurement agent
Tickmin25th%avgmedian75th%90th%95th%maxiqrstd dev# pairs
Mar2015151150.017996162.965944176175.121858173.904632185186.921939199201.620843208204.584698208204.5846982223.95699517.58613114
PingER VM Measurement agent

To N. America

PingerVM non VM measurement agent
Tickmin25th%avgmedian75th%90th%95th%maxiqrstd dev# pairs
Mar201523.095.312.54.89062.04279.31579.31579.31579.315.28.6783
PingER VM measurement agent 
Tickmin25th%avgmedian75th%90th%95th%maxiqrstd dev# pairs
Mar201523.095 41.35742.88862.07779.35079.35079.35061.77535.917 4

Correlation plots of pinger vs pingervm

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 for hourly measurements

Below are correlation plots of hourly PingER measurements between pinger.slac.stanford.edu and pingervm.slac.stanford.edu between Feb 26 and March 3rd, 2015.

Time series distributions

If one compares the average and median statistics for the tow sets of data, one gets the tables below:

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Looking at the above manually scaled plots of pinger>pingervm and pingervm>pinger together with it is apparent the RTTs from pinger to pingervm are > pingervm to pinger. Looking at the average, standard deviation, median and IQR tables and the differences between pinger as the monitoring site and pingervm as the monitoring site, we see :in tabular form (where the average errors are +- (stdev(pinger>pingervm)+stdev(pingervm>pinger)) and the median errors are +- (IQR(pinger>pingervm) + IQR(pingervm>pinger)). the Probabilities are those that the pinger>pingervm and pingervm>pinger distributions are the same (assuming normal distributions).

Diff (pinger-pingervm)min_RTT(ms)+-Probabilityavg_RTT(ms)+-Probabilitymax_RTT(ms)+-Probability
Average0.0584450.0855880.6826890.0742790.0921040.6826890.1125150.325707-0.99405
stdev0.005037  0.017744  0.21998  
median0.060.1405 0.070.11275 0.0850.15775 
IqR0.012  0.01425  0.00375  

It appears that the min_rtts, avg_rtts and max_rtts  are within 1 standard deviation (better than 68% assuming a normal distribution) of one another.

By looking at the cumulative distributions we can get the Median differences probability.