Table P-11 contains a time series of 96 monthly observations. Using a computer program for ARIMA modeling, obtain a plot of the data, the sample autocorrelations, and the sample partial autocorrelations. Develop an appropriate ARIMA model, and generate forecasts for the next 12 time periods from forecast origin t = 96.

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TABLE P-11 1 97.575 26 106,650 51 149,850 76 166950 97.755 27 122550 52 149.850 77 181,500 3 105,825 28 124,650 53 160350 78 173,925 4 104.700 29 128,925 54 161 325 79 174,450 5 110,700 30 26,038 55 153,225 80 179,475 6 108,060 3 129,300 159,375 81 180,300 7 111825 32 127,050 57 149,325 82 177,975 8 114,525 33 125,025 58 157.200 83 174,525 9 108375 34 129,675 59 63.350 84 220,650 10 117,900 35 134.25060 190,650 85 152,625 1 117,600 36 614756 1416008 143,100 12 142,800 3 115350 62 136,725 87 164.925 13 109,500 38 111.75063 158,625 88 167175 14 103,995 39 134,025 64 163,050 89 181.725 15 119.250 40 134.325 65 173925 90 174.150 16 121.200 41 140,175 6 165,90 91 174.675 17 123,900 42 144300 67 226,650 92 179.700 18 124.350 43 143.475 68 175.050 93 180.525 19 125.775 44 143,700 69 164.700 94 178200 20 126,900 45 140,325 70 167,625 95 174.750 21 121.650 46 144375 71 171,225 96 220,875 22 126,600 47 149,175 72 203.550 23 124.350 48 182,400 73 152,400 24 152,400 49 329074 142875 25 108,150 50 133,950 75 164,700