Question

screenshot MATlab code please

The following equation is available for the saturation pressure of air as a function of temperature: In (psat/Pc) = C1 x + C2 x? + C3 In (Tsat/Tc), where x = 1/Tc - 1/Tsat Pc =3.77 MPa is the critical pressure, and Tc = 132.5 K is the critical temperature. The following data are available for the saturation pressure of air as a function of temperature: Tsat (K) psat (MPa) Taat (K) paat (MPa) 76.5 80.4 83.3 85.7 88.1 90.2 92.0 93.6 95.1 96.5 98.9 0.08 0.12 0.16 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.60 101 103 106.3 109.2 111.8 114.2 116.4 118.4 122.9 127.0 0.70 0.80 1.00 1.20 1.40 1.60 1.80 2.00 2.50 3.00 Obtain the values of ci, c2 and cs from a least squares fit of the data. Analyze your regression fit by the computation of the standard error of the estimate, the coefficient of determination and the correlation coefficient.

Answer 1

Least square fit File Fit View Tools Desktop Window Help Fit name: Least square fit X data: х Y data: < y Z data: Z Weights: (none) > Results General model: f(x,y) = a*x + b*x^2 + c*y Coefficients (with 95% confidence bounds): a = 192.8 (142.2, 243.4) b = 5106 (4705, 5507) C= -0.09247 (-0.162,-0.02293) Goodness of fit: SSE: 6.638e-05 R-square: 0.9998 Adjusted R-square: 0.9998 RMSE: 0.00192

Here c1 = 192.8 , c2 = 5106 ,c3 = -0.09247.

Standard Error = 6.638e-05 which is very small.

Correlation coefficient (R^2)= 0.9998 i.e. very close to 1.

So, this fit is very good.