How to Linearize and Fit Data Points in MATLAB?

[hunter55]

Homework Statement

For the given set of data, find the least-square curve:
A) f(x)=Ce^Ax, by using the change of variable X=x, Y=ln(y), and C=e^B to linearize the data points.

B) f(x) = 1/(Ax+B), by using the change of variable X=x and Y = 1/y to linearize the data points.

x : [ -1 0 1 2 3]
y : [ 6.62 3.94 2.17 1.35 0.89]

I need the MATLAB code on how to do these 2 problems I am confused and which curve gives a better fit. ??

Homework Equations

This is the only code i know but idk how to do it with the question they are asking i need to pertain it to that

function C = poly(X,Y,M)
n=length(X);
B=zeros(1:M+1);
F=zeros(n,M+1);
for k=1:M+1
F(:,k)=X'.^(k-1);
end
A=F'*F;
B=F'*Y';
C=A\B;
C=flipud(C);

The Attempt at a Solution

These are the coefficients:
-0.0458x^3
0.5225x^2
-2.1567x
3.9040

I am confused with what the question is asking i know I am suppose to have a ans for part A and B

 

[Nok1]

Think about what a change of variable is, then figure out how to apply that to the data.

Aka, when you make a substitution for y=ln(y), that just means you take your y list, and just take the ln of that. That now because the new measurement for what used to be the y-axis.

Does that make sense?