Non-Polynomial Models ("Transforming" the Data) The four data points at right are measurements of the amount of mustard (y) left behind in a container as a function of the force (x) you squeezed the bottle. You2 want to calibrate an analytic model y-f(x) for future mustard-container analysis. You're considering the following five models for f(x) 6 i. f(x)-a+befor i. f(x)-4Pxefor three unknown coefficients P, Q ands . f(x)-uxfor three unknown coefficients u and w for two unknown coefficients a and b for two unknown coefficients a and k v.f(x)-XVr+9.8)*2 for two unknown coefficients X, and vo For EACH model (i) through (v), complete both tasks below (A) Write the problem out in matrix formray-Ac. Be sure to explicitly.. show me how you're analytically "transforming" the model (if necessary), define the vector c in terms of the unknown(s) in the model, write out the values of all the elements in the vector y and matrix A using the provided data (B) Use MATLAB to evaluate the least-squares best-fit c using the commandc A\y. evaluate the vector c, and all the unknown coefficients in the model (write each value to at least 4 significant figures), substitute the coefficients back into the general form to write out the final equation for the best-fit model f(x) Using MATLAB to solve for c-Ay, but everything needs to be written out