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Fundamentals of Probability and Statistics for Engineers

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Linear Models <strong>and</strong> Linear Regression 351y(x) l 2E(y) =^α^+ βxα^+ β ^ –x(x) l 1–xxFigure 11.4Confidence b<strong>and</strong> <strong>for</strong> EfYg ˆ ‡ xAnswer: equation (11.41) gives the desired confidence limits, with n ˆ 14, ˆ 0:05, <strong>and</strong>Efyg d ˆ^ ‡ ^x ˆ 0:63 ‡ 5:24x;t n 2;=2 ˆ t 12;0:025 ˆ 2:179; from Table A.4;x ˆ 11:11;X niˆ1…x i x† 2 ˆ 546:09;b 2 ˆ 182:10:The observed confidence limits are thus given by " #) l 1; 2 ˆ… 0:63 ‡ 5:24x†2:179 182:10 11=2…x 11:11†2‡ :14 546:09This result is shown graphically in Figure 11.5.11.1.5 SIGNIFICANCE TESTSFollowing the results given above, tests <strong>of</strong> hypotheses about the values <strong>of</strong> <strong>and</strong> can be carried out based upon the approach discussed in Chapter 10. Let usdemonstrate the underlying ideas by testing hypothesis H 0 : ˆ 0 againsthypothesis H 1 : 6ˆ 0 ,where0 is some specified value.TLFeBOOK

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