Queuing Models- Model 3

Does anyone know how they got .176 for Lq? The slide says that the Lq value for the model 3 problem is .176, but when I look at Exhibit 8A.9 with S=2 (The problem stated that there are 2 servers) and lambda/miu=.833 the chart says the value should be between .1523 and .1873. Even when I add them and divide by 2, my answer is still wrong. Could someone explain how to get .176? I attached Exhibit 8A.9 and the slide in reference.

Again, the given info is that there are 2 servers and lambda/miu= .833

NUMBER OF SERVICE CHANNELS, S / 1 1 2 3 5 6 7 8 9 10 11 12 13 14 15 0.10 0.01 0.15 0.0264 0.0006 0.20 0.0500 0.0020 0.25 0.0833 0.0039 0.30 0.1285 0.0069 0.35 0.1884 0.0110 0.40 0.2666 0.0166 0.45 0.3681 0.0239 0.0019 0.50 0.5000 0.0333 0.0030 0.55 0.6722 0.045 0.0043 0.60 0.9090 0.0593 0.0061 0.65 12071 0.0767 0.0084 0.70 1.6333 0.0976 0.0112 0.75 2.2500 0.1227 0.0147 0.80 3.2000 0.1523 0.0189 0.85 4.8165 0.1873 0.0239 0.0031 0.90 8.1000 0.2285 0.0300 0.0041 0.95 18.0500 0.2767 0.0371 0.0053 LO 0.3333 0.0454 0.0061 12 0.6748 0.0940 0.0158 14 13449 0.1778 0.0324 0.0059 16 2.8441 0.3128 0.0604 0.0121 18 7.6731 0.5320 0.1051 0.0227 2.0 0.8888 0.1730 0.0390 22 1.4907 0.2770 0.066 24 2.1261 0.4205 0.1047 2.6 4.9322 0.6581 0.1609 2.8 12.2724 1.0000 0.2411 3.0 1.5282 0.3541 32 2.3855 0.5128 3.4 3.9060 0.7365 3.6 7.0893 10550 3.8 16.9366 15181 4.0 2.2164 42 3.3269 4.4 5.2675 4.6 92885 4.8 216384 5.0 52 5.4 5.6 5.8 0.0084 0.0127 0.0047 0.0090 0.0158 0.0266 0.0065 0.0425 0.010 0.0659 0.0180 0.0991 0.0282 0.0077 0.1452 0.0427 0.0122 02085 0.0631 0.0189 0.2947 0.0912 0.0283 0.4114 0.1792 0.0412 0.5694 0.1801 0.0590 0.7837 0.2475 0.0827 10777 0.3364 0.1142 14857 0.4532 0.1555 2.0708 0.6071 0.2092 2.9375 0.8102 0.2785 43004 10804 0.3680 6.6609 14441 0.5871 11.5178 19136 0.6313 26.3726 26481 0.8225 3.6878 1.0707 5.2979 1.3967 8.0768 1.8040 13.7992 2.4198 311270 3.2441 0.0189 0.0273 0.0389 0.0541 0.0742 0.1006 0.1345 0.1779 0.2330 0.3032 0.3918 0.5037 0.6454 0.8247 10533 6.0 6.2 6.4 6.6 6.8 7.0 72 7.4 7.6 7.8 4.4471 6.3133 9.5102 16.0379 35.8956 13471 17288 2.2324 2.9113 3.8558 0.0087 0.0128 0.0184 0.0260 0.0361 0.0125 0.0492 0.0175 0.0663 0.0243 0.0085 0.0683 0.0330 0.0119 0.1964 0.0443 0.0164 0.1518 0.0590 0.0224 0.1964 0.0775 0.0300 0.0113 0.2524 0.1008 0.0398 0.0153 0.3222 0.1302 0.0523 0.0205 0.4090 0.1666 0.0679 0.0271 0.0105 0.5172 0.2119 0.0876 0.0357 0.0141 0.6521 0.2677 0.1119 0.0463 0.0187 0.8202 03364 0.1420 0.0595 0.0245 0.0097 10310 0.4211 0.1789 0.0761 0.0318 0.0129 12972 0.5250 0.2243 0.0966 0.0410 0.0168 16364 0.6530 0.2796 01214 0.0522 0.0220 2.0736 0.8109 0.3469 0.1520 0.0663 0.0283 2647010060 0.4288 0.1891 0.0834 0.0361 3.4160 12484 0.5236 0.2341 0.1043 0.0459 4.4805 1.5524 0.6501 0.2885 0.1208 0.0577 6.0183 19366 0.7980 0.3543 0.1603 0.0723 8.3869 24293 09788 0.4333 0.1974 0.0899 12.4183 3.0732 12010 0.5267 0.2419 0.1111 20.6160 3.9318 14752 0.5437 0.2952 0.1367 45.4769 5.1156 18165 0.7827 0.3699 0.16731 6.8210 2.2465 0.9506 0.4352 0.2040 8.0 82 8.4 86 8.8 5.2264 7344 10.9592 18.3223 40.6824 9.0 92 9.4 9.6 9.8 10 From the table, using linear interpolation and N/u = 0.833 = Lq = 0.176