Suppose that there is a specimen with X1 = 9, X2 = 2.0 and X3 = 83, estimates the strain of the specimen as well as its 95% confidence interval.

EXST7014 lab5, Marquetetta Anderson, Section# Full model of multi-linear regression fitted by using PROC REG The REG Procedure Model: Full Dependent Variable: y2 Output Statistics Std Error Dependent Predicted Mean Obs Variable Value Predict 95% CL Mean 95% CL Predict Residual 1 2 3.20 3.5377 1.1144 1. 1626 5.9129 -1.7965 8.8719 -0.3377 3 0.73 0.2441 1.0190 -1.9279 2.4161 -5.0028 5.4910 0.4859 4 0.16 -2.0980 1.1846 -4.6228 0.4268 -7.5005 3.3045 2.2580 5 1.44 1.5590 1.0452 -0.6687 3.7868 -3.7112 6.8292 -0.1 190 6 3.68 4.9842 0.7295 3.4293 6.5392 -0.0387 10.0072 -1.3042 3.11 4.8703 1.0991 2.5275 7.2131 -0.4496 10. 1901 -1.7603 3.07 2.8941 0.9408 0.8889 4.8993 -2.2860 8.0742 0.1759 9 0.19 -0.3995 1.0082 -2.5485 1.7495 -5.6369 4.8379 0.5895 10 0.00 -2.7417 1.2726 -5.4541 -0.0292 -8.2343 2.7510 2.7417 11 5.86 7.3163 1.0201 5.1420 9.4906 2.0685 12.5641 -1.4563 12 5.97 5.3401 0.7683 3.7025 6.9777 0.2910 10.3893 0.6299 13 0.29 2.0465 0.7138 0.5250 3.5680 -2.9662 7.0592 -1.7565 14 0.04 -0.2957 0.9806 -2.3858 1.7945 -5.5092 4.9179 0.3357 15 2.72 4.2292 1.0179 2.0595 6.3989 -1.0167 9.4751 -1.5092 16 7.35 8.0103 0.9088 6.0732 9.9473 2.8562 13.1643 -0.6603 17 1.17 4.7166 0.9628 2.6645 6.7688 -0.4818 9.9151 -3.5466 18 0.14 2.3745 1.2281 -0.2432 4.9922 -3.0720 7.8210 -2.2345 19 15.00 9.9865 1.0804 7.6837 12.2892 4.6841 15.2888 5.0135 20 11.80 9.3454 1.2171 6.7511 11.9396 3.9101 14.7807 2.4546