CPE121 Lect05InClass S08 (version 1)

CPE121 Lect05InClass S08 (version 1) - Beta =(X T X-1 X T...

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Measured values xexp yexp 1 13.50 2 19.61 3 42.22 4 66.38 5 88.99 6 118.67 7 130.08 8 174.83 9 220.48 10 252.57 Straight Line fit X ycalc Resids x 1 XBeta 1 1 -8.40 21.90 1 2 3 4 2 1 18.52 1.09 1 1 1 1 3 1 45.44 -3.22 4 1 72.36 -5.97 5 1 99.27 -10.28 6 1 126.19 -7.53 0.01 -0.07 7 1 153.11 -23.03 -0.07 0.47 8 1 180.03 -5.20 9 1 206.95 13.53 10 1 233.86 18.70 Sum 0 m1 26.92 Using Linest b -35.32 m1 b 26.92 -35.32 1.64 10.19 0.97 14.91 268.78 8 ### 1779.2 Quadratic Fit X ycalc Resids X T y exp - y calc (X T X) -1 Beta = (X T X) -1 X T yexp X T 0 2 4 6 8 10 -100 -50 0 50 100 150 200 250 300 f(x) = 26.92x - 35.32 R² = 0.97 Linear Regression Example Column B Linear Re- gression for Column B Column C x y
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x 1 XBeta 1 1 1 11.578 1.92038219831188 1 4 9 16 4 2 1 25.178 -5.56690484686322 1 2 3 4 9 3 1 42.108 ### 1 1 1 1 16 4 1 62.367 4.0153584667346 25 5 1 85.955 3.03625363289241 36 6 1 112.873 5.79219441864217 49 7 1 143.121 -13.0388683446241 0 -0.02 0.04 64 8 1 176.698 -1.86878081925011 -0.02 0.24 -0.53 81 9 1 213.604 6.87080816161068 0.04 -0.53 1.38 100 10 1 253.840 -1.27372299051439 Sum 0.000 Using Linest m2 m1 b 8.61 1.66 1.31 m1 1.66 3.3 0.29 7.9 m2 8.61 0.99 6.72 #N/A b 1.31 678.48 7 #N/A ### 315.92 #N/A x 2 y exp - y calc (X T X) -1
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Unformatted text preview: Beta = (X T X)-1 X T yexp 5 6 7 8 9 10 1 1 1 1 1 1 12 25 36 49 64 81 100 5 6 7 8 9 10 1 1 1 1 1 1 z = a*exp(cx) Measured values yexp ycalc Resids zcalc x zexp ln(zexp) m1(x)+b yexp - yexp(ycalzexp - zcalc 0.0 3.85 1.35 1.37-0.02 1.85 0.2 4.76 1.56 1.67-0.11 2.61 0.4 7.41 2 1.97 0.03 3.95 0.6 10.48 2.35 2.27 0.08 5.34 0.8 13.88 2.63 2.58 0.05 6.78 1.0 18.79 2.93 2.88 0.06 8.44 1.2 23.11 3.14 3.18-0.04 9.98 1.4 32.55 3.48 3.48 12.12 1.6 44.64 3.8 3.78 0.02 14.37 1.8 55.98 4.02 4.08-0.06 16.44 2.0 80.00 4.38 4.39 19.22 Using Linest m1 b 1.51 1.37 c = m1 = 0.03 0.03 a = exp(b) = 1 0.06 2940.47 9 10.02 0.03 ln(z)=ln(a)+cln(w) z=aw C 0.0 0.5 1.0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 f(x) = 1.51x + 1.37 R² = 1 X ln(z) 1.5 2.0 2.5 Column C Linear Regression for Column C...
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This note was uploaded on 04/30/2008 for the course C&PE 121 taught by Professor Howat during the Spring '08 term at Kansas.

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CPE121 Lect05InClass S08 (version 1) - Beta =(X T X-1 X T...

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