Cubic Regression Calculator

Find the cubic polynomial of best fit for $$$\left\{\left(-2, -7\right), \left(-1, -1\right), \left(0, 0\right), \left(1, 2\right), \left(2, 5\right)\right\}$$$.

The number of observations is $$$n = 5$$$.

Generate the following matrix $$$M = \left[\begin{array}{cccc}\left(-2\right)^{3} & \left(-2\right)^{2} & -2 & 1\\\left(-1\right)^{3} & \left(-1\right)^{2} & -1 & 1\\0^{3} & 0^{2} & 0 & 1\\1^{3} & 1^{2} & 1 & 1\\2^{3} & 2^{2} & 2 & 1\end{array}\right].$$$

Generate the following vector $$$Y = \left[\begin{array}{c}-7\\-1\\0\\2\\5\end{array}\right]$$$.

The vector of coefficients is $$$X = \left(M^T M\right)^{-1}M^T Y = \left[\begin{array}{c}\frac{1}{2}\\- \frac{5}{14}\\1\\\frac{18}{35}\end{array}\right]$$$.

Thus, the cubic polynomial of best fit is $$$y = \frac{x^{3}}{2} - \frac{5 x^{2}}{14} + x + \frac{18}{35}$$$.

The cubic polynomial of best fit is $$$y = \frac{x^{3}}{2} - \frac{5 x^{2}}{14} + x + \frac{18}{35}\approx 0.5 x^{3} - 0.357142857142857 x^{2} + x + 0.514285714285714.$$$A