ulations are reliable and stable giving a sufficient confidence. For the same scenario, the confidence intervals for the packet loss ratios in the transport network were also investigated in Figure A.38. The graph shows the packet loss ratios and their 95% CI over different loads. Same as above, every point of the curve represents the mean packet loss ratio of 8 different seeds simulations. The calculations of the confidence intervals are same as above. Appendix 95% Confidence margin of relative application Interval for the mean (normalized) error (s) margin of delay (s) application delay (s) error 4.5517 [4.5409, 4.5625] 0.0108 0.0024 4.8119 [4.7739, 4.8499] 0.038 0.0079 5.6766 [5.5759, 5.7773] 0.1007 0.0177 7.722 [7.474, 7.97] 0.248 0.0321 10.7047 [10.3602, 11.0492] 0.3445 0.0322 Table A.10: 95% CI for application delays of a 50kbyte web page (RAB 128kbps) Confidence Interval of the transport network packet loss ratio of elastic traffic Figure A.38: Packet loss ratio with 95% CI: web scenario, RAB 128 kbps, no CAC, constant file size of 50 kbyte, lub link = 1 E1 line (ATM) Similarly, the 95% confidence intervals were also investigated for the CAC connection reject ratio (see Figure A.39) for the circuit-switched voice traffic. For each point shown in the graph, 8 simulation runs were performed and each run with a different random seed. The graph also shows that the confidence intervals get wider in higher loads. A.21 Statistical Evaluation: Limited Relative Error Confidence Interval of the CAC reject ratio of voice traffic offered voice traffic demand [kbps] Figure A.39: CAC reject ratio with 95% CI: voice scenario, lub link = 1 Mbps (ATM) In all investigated example scenarios, the obtained confidence intervals for different QoS measures have demonstrated that the simulation results are reliable and confident (with relative margin of error <10%). A.21 Statistical Evaluation: Limited Relative Error The Limited Relative Error (LRE) is another important statistical evaluation method to evaluate the statistical sig