how can we linearise?

Linearise the given nonlinear equation and then apply linear least-squares regression to find the equation

for the regression line. Plot the linearised data set together with the regression line. Determine Sr (the sum

of squares of residuals around the regression line) and r2 (the corresponding coefficient of determination).

clc
clear all
close all
syms x y a b A B a0 a1     
%given dependent and independent datas
xdata=[0.1 0.2 0.4 0.6 0.9 1.3 1.5 1.7 1.8];
ydata=[0.75 1.25 1.45 1.25 0.85 0.55 0.35 0.28 0.18];




sr=ydata-(a.*xdata.*exp(b.*xdata))
%Finding the values of Sr,St,a,b,r-square
A=diff(sr,a0);
B=diff(sr,a1);

sr=sum(ydata-(a.*xdata.*exp(b.*xdata)))
st=sum((ydata-mean(ydata)).^2);
r2=(st-sr)./st;
display(sr)
display(r2)
display(st)