A MATLAB code is given below in order to plot data from a lab exercise:

idmeas=[0.068 0.726 3.56 13.19 31.5 63.4 99.9]; %All measured id values in mA vgsmeas=[2.0 2.2 2.4 2.6 2.8 3.0 3.2]; %All measured vgs values idfit=[0 0 0 0]; %Measured id values used for curve fit vgsfit=[0 0 0 0]; %Measured vgs values used for curve fit p=polyfit(vgsfit,idfit,2); %Find 2nd order polynomial coefficients vgs1=[0:0.02:3.5]; %vgs range for parabola calculation, increment=0.02V id1=polyval(p,vgs1); plot(vgsmeas,idmeas,'*',vgs1,id1) %Points only for meas, line for calc axis([1 3.5 0 120]) %Typical axis settings, you can change xlabel('Vgs, V') ylabel('Id, mA') grid

a.) Fit the curve to a parabola. Edit the graph to show the parabola curve. Extract the parabola's coefficients given by the the array variable p.

b.) Plot the measured data from Tables 2 and 3 on the one graph of I_D vs. V_DS in part a. Use linear regression analysis on each plot separately to find best-fit lines matching the data.

Table 2:

VDS	1	2	3	4	5	6	7	8	9	10
ID	12.7	13.15	13.613	14.134	14.703	15.337	15.96	16.675	17.385	18.225

Table 3:

VDS	1	2	3	4	5	6	7	8	9	10
ID	24.350	25.420	26.55	27.875	29.355	30.456	32.332	33.977	36.385	38.759

Please help!!! And please provide the two codes.