saturation - growth - rate : y =3(x/(3 + x)) from lecture

5. Use the function hirreg. m to perform lincar least squares regression on the data given FIGURE 14.15 An M-file to implement linear regression. below. In ivireg a0 is the intercept and al is the slope. In addition, the inreg function has a third output variable which is the correlation coefficient r. Use the regression code for two types of curve fits: 1) linear and 2) the nonlinear saturation model given is the lecture noles. For the second case, inelude the formulation on how to use linear least squares regression to fit the data to the nonlinear saturation model. Use the value of the correlation coefticient to evaluate which fitting function better fits the data. Plot the individual data points and the two types of curve fits (linear as a dashed line and saturation as s solid curvej on one graph