For completeness I'll show you how this is solved in general. It's not trivial
\(\text{first we construct the matrix}\\ X = \begin{pmatrix}1 &x_1 &x_1^2\\1 &x_2 &x_2^2\\\vdots\\1 &x_n &x_n^2\end{pmatrix}\)
\(\text{In this problem this is}\\ X=\left( \begin{array}{ccc} 1 & 1 & 1 \\ 1 & 2 & 4 \\ 1 & 3 & 9 \\ 1 & 4 & 16 \\ 1 & 5 & 25 \\ 1 & 6 & 36 \\ \end{array} \right)\)
\(\text{We then form the matrix}\\ Y=\begin{pmatrix}y_1\\y_2\\\vdots \\ y_n\end{pmatrix}\\ \text{In this problem this is}\\ (32, 78, 178, 326, 390, 337)^T\)
\(\text{The equation for the coefficients of the least squares quadratic fit is given by}\\ c = (X^TX)^{-1}X^TY\)
\(\text{Grinding this through we get}\\ c =(-143.9,154.418,-11.4107)^T \text{ i.e. that the best fit quadratic is}\\ y(t) = -11.41t^2 + 154.42x - 143.9\)
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