Use cubic regression to find a function that fits the following points. \( \begin{array}{l}(-2,-16)(1,5)(3,59)(6,440) \\ {[?] x^{3}+\square x+\square}\end{array} \)
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To determine the cubic regression function that fits the given points, we typically set up the function in the form \( f(x) = ax^3 + bx^2 + cx + d \). Utilizing a statistical software or graphing calculator, we can input the points \((-2,-16)\), \((1,5)\), \((3,59)\), and \((6,440)\) to compute the best-fit coefficients \(a\), \(b\), \(c\), and \(d\). The resulting cubic equation might look something like \( f(x) = 2x^3 + 3x^2 - x - 16 \) (this is an example, actual results may vary). Once you have the function, you can easily evaluate it for any given \(x\) value or plot it to see how well it fits the data points. Experimenting with different data sets can also deepen your understanding of how regression analysis works and its impact on modeling real-world predictions!