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Spreadsheet of min/avg/max and loss between and from pinger & pi to & from sitka, and to cern, plus probabilities, IPDV.
Spreadsheet of probabilities and IPDV from SLAC to TRIUMF
However the ping distributions are decidedly non-normal (see for example the figure below) have wide outliers, and are heavy tailed on the upper side (see https://www.slac.stanford.edu/comp/net/wan-mon/ping-hi-stat.html). This leads to large standard deviations (one to two order of magnitude greater than the IQR) in the RTT values. As can be seen from the table this results in low values of the Z-test and a false probability of no significant statistical difference. Using the IQRs of the frequency distributions instead generally leads to much higher values of the Z-test and hence a higher probability that the distributions of RTTs between two pairs of hosts are significantly different. Comparing the frequency distributions it is seen that there is indeed a marked offset in the RTT values of the peak frequencies and a resultant difference in the cumulative RTT distributions, Using the non-parametric Kolomogorov Smirnoff test (KS test) also indicated significant differences in the distributions.
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PingER's main metric for measuring jitter is the IPDV. A typical IPD distribution from which the IPD is derived is shown below.
IPD distributions are centered on 0ms and have very wide tails. The one in the figure is cut off below the 2 percentile and above the 98% percentile. The number of outliers not shown is given in the figure, as are the maximum and minimum values of IPD. The distribution is thus seen to have very positive and negative tails. Also as illustrated in the figure a typical IPD distribution has a very sharp peak. To derive the IPDV we take the IQR of the IPD dsitribution. The values for the IPDV for the various measurements are shown in the followjng table; The errors(S) in the IPD are taken from the IQR for the hourly PingER IPDVs observed for the same period. It is seen that the Z-Test in this indicates a value of < 2.0. Assuming the Z-Test is relevant for the non-normal IPD distributions if one uses the IQRs instead of the standard deviation, a value of < 2 for the Z-test statistics indicates the two samples are the same (see http://homework.uoregon.edu/pub/class/es202/ztest.html.
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