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. You want to calibrate an analytic model y -f(x) for future mustard-container analysis You're considering the following five models for f(x) f(x)- a+be" m. f(x)- 4Px iii. f(x)-2 + wx for two unknown coefficients a and b for three unknown coefficients P, Q and S thr 1 for two unknown coefficients u and w IV for two unknown coefficients a and k f(x)-XVx+(9.8) x for two unknown coefficients X, and Vo For EACH model (i) through (v), complete both tasks below (A) Write the problem out in matrix form r-y-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 command c -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)