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Since the timestamps of measurements for one MA to a target are not synchronized with another MA to the same target, they are sampling the network at different times. Thus we decided not to use the residuals in the RTTs between on one pair and another. Typically the difference in the time of a measurement from say pinger.slac.stanford.edu to sitka.triumf.ca versus pinger-raspberry.slac.stanford.edu to sitka.triumf.ca averages at 8 mins (see spreadsheet).To find the probability of the distributions overlapping we can use a nomogram of mean differences versus error ratios given in Overlapping Normal Distributions. John M. Linacre for normal distributions. However this does not cover the range we are interested in.
We also use therefore used the Z Tests to compare two samples, see for example “Comparing distributions: Z test” available at http://homework.uoregon.edu/pub/class/es202/ztest.html
Kolmogorov-Smirnov Test
The Kolmogorov-Smirnov test (KS-test) tries to determine if two datasets differ significantly. The KS-test has the advantage of making no assumption about the distribution of data. In other words it is non-parametric and distribution free. The method is explained here and makes use of an Excel tool called "Real Statiscs". The tests were made using the raw data and distributions, both methods had similar results except for the 100Bytes Packet that had a great difference in the results. The results using raw data says both samples does not come from the same distribution with a significant difference, however if we use distributions the result says that only the 1000Bytes packet does not come from the same distribution. Bellow Below you will find the graphs for the distributions that were created and the cumulative frequency in both cases plotted one above other (in order to see the difference between the distributions).
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