clear all
close all
clc
% Preparing the data
cp_data=load(\'data.txt\');
temperature=cp_data(:,1);
cp=cp_data(:,2);
% Curve fit
% cp= aT^2 + b*T + c
coeffs= polyfit(temperature,cp,4);
predicted_cp= polyval(coeffs , temperature);
% compare curve fit with original data
plot(temperature,cp,\'linewidth\',2);
hold on
plot(temperature,predicted_cp,\'linewidth\',3,\'color\',\'r\');
xlabel(\'Temperature [K]\');
ylabel(\'Specific Heat [KJ/Kmol-K]\');
legend(\'Original data\',\'Curve fit\')
EXPLAINATION
The result i got is for cubic curve which is some what following the original data curve
,it is not very accurate .Thus the result i got is somewhat appropriate.
In order to improve the result we can simply increase the degree of the polynomial,as we increase the degree of polynomial the predicted cp follows the ori=ginal data more accuratly ,thus if we increase the degreee of polynomial then we get better result and at certain degree it is exactly as original data and increasing the degree results in no changes.