A complete second order regression model in the variables x1 and x2 is given by y = α + β1x1 + β2x2 + β3x12 + β4x22 +
e.
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Q7: The estimated regression function Q8: The predicted values, the residuals and SSResid Q9: The alternative hypothesis in the model utility Q10: A variable taking on only the values Q11: The least squares estimate of β1 is Q13: It is possible to carry out the Q14: In a multiple regression model, the utility Q15: The polynomial regression model used to fit Q16: In the quadratic regression model, y = Q17: A general additive multiple regression model has![]()
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