Linear Least Squares Regression

x = [2, -2, 3, -3];
y = [7, 8, 19, 17]; 
N = length(x);
X = 'ones (N, 1), x';
Y = y;
J='inv(X.*X)*X*Y';
plot(x,y,'bs',[0, 5],J(1)+J(2)*[0, 5]+J(3)*[0, 5]);
hold on

how can i turn this graph into this graph 

Answer 1

[Bora Eryilmaz]

% Original data
x = [2, -2, 3, -3];
y = [7, 8, 19, 17]; 

% Take tranposes.
x = x';
y = y';

% Find coefficients of a quadratic polynomial fit using linear least
% squares method.
C = [x.^2 x ones(size(x))] \ y

C = 3×1

2.1000 0.1538 -0.9000

% Get interpolated values on the polynomial.
xi = (-4:0.1:4)';
yi = C(1)*xi.^2 + C(2)*xi + C(3);

% Plot results.
plot(x,y, 'r*')
hold on
plot(xi,yi,'b-')

[A]

thank bro