Quadratic least square regression also referred to as non-linear regression, second order regression or simply quadratic...

 

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Quadratic least square regression also referred to as non-linear regression, second order regression or simply quadratic regression is the process of finding the equation of a parabola that best fits a set of data. As a result, we get an equation of the form: y=ax²+bx+c where a#0 Problem Statement: The table below shows the thermal expansion coefficient of steel over a range of temperature. Compute the quadratic regression and check its fitness by calculating the value of correlation coefficient. Write down the complete procedure/calculations (by hand). Thermal Expansion Coefficient (Hin/in/°F Temperature F 80 60 40 20 0 -20 -40 -60 -80 -100 -120 -140 -160 -180 -200 -220 -240 -260 -280 -300 -320 -340 6.47 6.36 6.24 6.12 6.00 5.86 5.72 5.58 5.43 5.28 5.09 4.91 4.72 4.52 4.30 4.08 3.83 3.58 3.33 3.07 2.76 2.45 Quadratic least square regression also referred to as non-linear regression, second order regression or simply quadratic regression is the process of finding the equation of a parabola that best fits a set of data. As a result, we get an equation of the form: y=ax²+bx+c where a#0 Problem Statement: The table below shows the thermal expansion coefficient of steel over a range of temperature. Compute the quadratic regression and check its fitness by calculating the value of correlation coefficient. Write down the complete procedure/calculations (by hand). Thermal Expansion Coefficient (Hin/in/°F Temperature F 80 60 40 20 0 -20 -40 -60 -80 -100 -120 -140 -160 -180 -200 -220 -240 -260 -280 -300 -320 -340 6.47 6.36 6.24 6.12 6.00 5.86 5.72 5.58 5.43 5.28 5.09 4.91 4.72 4.52 4.30 4.08 3.83 3.58 3.33 3.07 2.76 2.45

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We compute the quadratic regression and check its fitness by cal... View the full answer