2 variables 90 observations for check of v[ 0][ 0] = -0.2437 for check of v[ 0][ 1] = -0.8898 for check of v[ 0][ 2] = -0.3858 for check of v[ 1][ 0] = -0.4678 for check of v[ 1][ 1] = 0.4563 for check of v[ 1][ 2] = -0.7570 for check of v[ 2][ 0] = -0.8496 for check of v[ 2][ 1] = 0.0040 for check of v[ 2][ 2] = 0.5274 for i= 0 and j= 0 check summation of Vki*Vkj = 1.0000 for i= 0 and j= 1 check summation of Vki*Vkj = 0.0000 for i= 0 and j= 2 check summation of Vki*Vkj = -0.0000 for i= 1 and j= 0 check summation of Vki*Vkj = 0.0000 for i= 1 and j= 1 check summation of Vki*Vkj = 1.0000 for i= 1 and j= 2 check summation of Vki*Vkj = 0.0000 for i= 2 and j= 0 check summation of Vki*Vkj = -0.0000 for i= 2 and j= 1 check summation of Vki*Vkj = 0.0000 for i= 2 and j= 2 check summation of Vki*Vkj = 1.0000 w[ 0] = 11.1493 sigma[0] **2 = 1.2541 w[ 1] = 0.8476 sigma[1] **2 = 0.8746 w[ 2] = 0.9914 sigma[2] **2 = 0.2889 epsilon/y for data i = 0 is = 0.0422 epsilon/y for data i = 1 is = 0.0767 epsilon/y for data i = 2 is = -0.9006 epsilon/y for data i = 3 is = -0.7986 epsilon/y for data i = 4 is = 0.3354 epsilon/y for data i = 5 is = -0.2875 epsilon/y for data i = 6 is = -1.1837 epsilon/y for data i = 7 is = -0.0193 epsilon/y for data i = 8 is = -0.0248 epsilon/y for data i = 9 is = -0.0177 epsilon/y for data i = 10 is = 0.2962 epsilon/y for data i = 11 is = 0.0264 epsilon/y for data i = 12 is = 0.0493 epsilon/y for data i = 13 is = 0.0665 epsilon/y for data i = 14 is = 0.1243 epsilon/y for data i = 15 is = -0.1908 epsilon/y for data i = 16 is = -0.0257 epsilon/y for data i = 17 is = 0.2775 epsilon/y for data i = 18 is = 0.0241 epsilon/y for data i = 19 is = -0.0098 epsilon/y for data i = 20 is = 0.1726 epsilon/y for data i = 21 is = 0.2905 epsilon/y for data i = 22 is = -0.1233 epsilon/y for data i = 23 is = 0.0181 epsilon/y for data i = 24 is = -0.1874 epsilon/y for data i = 25 is = 0.1051 epsilon/y for data i = 26 is = 0.3925 epsilon/y for data i = 27 is = 0.0876 epsilon/y for data i = 28 is = -0.1687 epsilon/y for data i = 29 is = -0.0650 epsilon/y for data i = 30 is = -0.0207 epsilon/y for data i = 31 is = -0.5976 epsilon/y for data i = 32 is = -1.1955 epsilon/y for data i = 33 is = 0.0276 epsilon/y for data i = 34 is = -0.1590 epsilon/y for data i = 35 is = -0.4035 epsilon/y for data i = 36 is = 0.0098 epsilon/y for data i = 37 is = 0.0031 epsilon/y for data i = 38 is = 0.2143 epsilon/y for data i = 39 is = 0.1231 epsilon/y for data i = 40 is = 0.0200 epsilon/y for data i = 41 is = 0.0391 epsilon/y for data i = 42 is = 0.0402 epsilon/y for data i = 43 is = 0.1967 epsilon/y for data i = 44 is = -0.3402 epsilon/y for data i = 45 is = -3.3974 epsilon/y for data i = 46 is = 0.0877 epsilon/y for data i = 47 is = -0.0621 epsilon/y for data i = 48 is = 0.0499 epsilon/y for data i = 49 is = -0.1199 epsilon/y for data i = 50 is = -0.0792 epsilon/y for data i = 51 is = -0.0218 epsilon/y for data i = 52 is = 0.0396 epsilon/y for data i = 53 is = 0.0083 epsilon/y for data i = 54 is = 0.0083 epsilon/y for data i = 55 is = -0.0412 epsilon/y for data i = 56 is = 0.1164 epsilon/y for data i = 57 is = -0.0379 epsilon/y for data i = 58 is = -0.0432 epsilon/y for data i = 59 is = -0.0433 epsilon/y for data i = 60 is = 0.0227 epsilon/y for data i = 61 is = -0.6715 epsilon/y for data i = 62 is = 0.0606 epsilon/y for data i = 63 is = 0.0417 epsilon/y for data i = 64 is = 0.0539 epsilon/y for data i = 65 is = -0.0072 epsilon/y for data i = 66 is = 0.3579 epsilon/y for data i = 67 is = -0.1103 epsilon/y for data i = 68 is = 0.0614 epsilon/y for data i = 69 is = 0.0383 epsilon/y for data i = 70 is = -0.0582 epsilon/y for data i = 71 is = 0.0728 epsilon/y for data i = 72 is = 0.1270 epsilon/y for data i = 73 is = -0.0531 epsilon/y for data i = 74 is = -0.0243 epsilon/y for data i = 75 is = -0.1044 epsilon/y for data i = 76 is = -0.0860 epsilon/y for data i = 77 is = -0.0971 epsilon/y for data i = 78 is = 0.0615 epsilon/y for data i = 79 is = 0.0182 epsilon/y for data i = 80 is = -0.3486 epsilon/y for data i = 81 is = 0.0414 epsilon/y for data i = 82 is = -0.0890 epsilon/y for data i = 83 is = -0.0055 epsilon/y for data i = 84 is = 0.0312 epsilon/y for data i = 85 is = 0.0788 epsilon/y for data i = 86 is = -0.1048 epsilon/y for data i = 87 is = 0.1182 epsilon/y for data i = 88 is = -0.0100 epsilon/y for data i = 89 is = -1.2977 SSresid = 1.3702 standard residiance = 0.1233864495 mean y = 0.8082 SSto = 6.5147 standard variance of y = 0.2690 F = 168.9590 standard deviation = 0.1255 R ** 2 = 0.7897 adjusted R ** 2 = 0.7897 ------------------------------------------ a[0]=-2.53869 a[1]=0.473378 a[2]=1.2706 a[3] has w == 0 r = 0.888639; r^2 = 0.789679; t = 18.1771