function P3_03D2
clear, clc, format short g, format compact
xyData=[85.47	2.48E+07
90	2.46E+07
100	2.42E+07
110	2.37E+07
120	2.33E+07
130	2.29E+07
140	2.25E+07
150	2.21E+07
160	2.17E+07
170	2.13E+07
180	2.09E+07
190	2.05E+07
200	2.01E+07
210	1.97E+07
220	1.93E+07
231.07	1.88E+07
240	1.83E+07
250	1.78E+07
260	1.73E+07
270	1.67E+07
280	1.61E+07
290	1.54E+07
300	1.46E+07
310	1.38E+07
320	1.28E+07
330	1.18E+07
340	1.05E+07
350	8.95E+06
360	6.81E+06];
X=xyData(:,1);
m=size(X,1); %Determine the number of data points
Y=xyData(:,2);
prob_title = ([' Heat of Vaporization of Propane, NlN Reg.']);
dep_var_name=['Heat of Vaporization (J/kmol) '];
ind_var_name=['Temperature (K)'];
parm=[2.926e6 0.3765];
npar=size(parm,2); % Determine the number of the parameters
options=optimset('MaxFunEvals',1000); % Change the default value for MaxFunEvals
Beta=fminsearch(@NonlinFun,parm,options,X,Y); % Find optimal parameters using fminsearch
[f,Ycalc]=NonlinFun(Beta,X,Y); % Compute Y (calculated) at the optimum
disp(['   Results,' prob_title ]); 
Res=[];
for i=1:npar
	Res=[Res; i Beta(i)];
end
disp('     Parameter No.   Value      ');
disp(Res);
s2=sum((Y-Ycalc)'*(Y-Ycalc))/(m-npar); %variance 
disp(['  Variance ', num2str(s2)]);	
ymean=mean(Y);
R2=(Ycalc-ymean)'*(Ycalc-ymean)/((Y-ymean)'*(Y-ymean));%linear correlation coefficient
disp(['  Correlation Coefficient ', num2str(R2)])	
plot(Y,Y-Ycalc,'*')	% Residual plot			
title(['Residual Plot, ' prob_title ])				
xlabel([dep_var_name '(Measured)'])				
ylabel('Residual')				
pause
plot(X,Ycalc,'r-',X,Y,'b+' ) %Plot of experimental and calculated data						
title(['Calculated/Experimental Data ' prob_title])						
xlabel([ind_var_name])						
ylabel([dep_var_name])
function [f,Ycalc]=NonlinFun(parm,X,Y)
A=parm(1);
n=parm(2);
for i=1:size(X,1);
Ycalc(i,1)=A*(369.83-X(i))^n;
end
resid(:,1)=Y-Ycalc;
f=resid'*resid;