HP 40gs HP 39gs_40gs_Mastering The Graphing Calculator_English_E_F2224-90010.p - Page 135
Obtaining coefficients from the fit model, Finding Fit Coefficients
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Obtaining coefficients from the fit model The function PREDY from MATH gives a predicted y value using the last line of best fit that was calculated. This means that you must use the SYMB view to ensure that your set of data is the only one ed and make sure SYMB SETUP is set to the correct fit model, and also use the PLOT screen and the key to ensure that your set of data was the last one graphed and that it has had its curve of best fit displayed. Until the curve has been displayed, the coefficients are not available or, worse, might belong to another data set. If you want to gain access to the PREDY function algebraically then the simplest way to do this is to enter F1(X)=PREDY(X) into the Function aplet, highlight it and press . The equation will be transferred and can then be analyzed using the normal Function tools. If you want individual coefficients they can also be obtained from the chosen fit model algebraically. For example, if the line of best fit is y = m * X + b and the fit line is showing in the SYMB screen as below then the calculations shown right will give the slope and y-intercept. PREDY (0) = m *0 + b = b and PREDY (1) − PREDY (0) = (m *1+ b) − (m *0 + b) = m + b − b = m Finding Fit Coefficients Linear Logarithmic Exponential Power Quadratic - m*X+b b = PREDY(0) m = PREDY(1)-PREDY(0) - m*LN(X)+b b = PREDY(1) m = PREDY(e)- PREDY(1) - b*EXP(m*X) b = PREDY(0) m = LN(PREDY(1)/PREDY(0)) - b*X^m b = PREDY(1) m = LN(PREDY(e)/PREDY(1)) - a*X^2+b*X+c or, a = (PREDY(2)-2*PREDY(1)+PREDY(0))/2 b = (PREDY(2)+4*PREDY(1)-3*PREDY(0))/2 c = PREDY(0) ⎡a⎤ ⎡0 0 1⎤−1 ⎡PREDY (0)⎤ ⎢⎢b 1 1 1⎥⎥ × ⎢ ⎢ PREDY (1) ⎥ ⎥ ⎢⎣c 4 2 1 PREDY (2)⎦⎥ 135