use 1st, 2nd and 3rd degree of polynomials to fit price1 vs index in matlab

main.m
% Sample data
index = [1, 2, 3, 4, 5];
price1 = [10, 12, 14, 16, 18];

% Plot original data
plot(index, price1, 'o');

hold on;

% Fit first degree polynomial
p1 = polyfit(index, price1, 1);
f1 = polyval(p1, index);
plot(index, f1);

% Fit second degree polynomial
p2 = polyfit(index, price1, 2);
f2 = polyval(p2, index);
plot(index, f2);

% Fit third degree polynomial
p3 = polyfit(index, price1, 3);
f3 = polyval(p3, index);
plot(index, f3);

% Add plot labels and title
xlabel('Index')
ylabel('Price1')
title('Polynomial Regression')

% Add plot legend
legend('Data', '1st Degree Polynomial', '2nd Degree Polynomial', '3rd Degree Polynomial')
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