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We 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
Spreadsheet of min/avg/max loss between and from pinger & pi to & from sitka, and to cern, plus probabilities, IPDV,
Powerpoint of figures.
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. 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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