When each independent variable is changed by one unit, use linear regression to get the mean change in the dependent variable. Polynomials can be used to simulate curvature as well as to add interaction effects.
An entire second order model is what?
The x1 and x2 linear terms, the x12 and x22 second-degree terms, and the x1x2 interaction term make up the entire second degree polynomial model. As could be used to represent the estimated model.
Which kind of model would you apply to discover the relationship between the dependent and independent variables?
Considering a one-unit change in each independent variable, use linear regression to determine the mean change in a dependent variable. To represent curvature and take interaction effects into account, you may also employ polynomials.
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The complete question is "Consider a regression analysis with three independent variables x1,x2, and x3. Give the equation for the following regression models: a. The model that includes as predictors all independent variables but no quadratic or interaction terms. b. The model that includes as predictors all independent variables and all quadratic terms. c. All models that include as predictors all independent variables, no quadratic terms, and exactly one interaction term. d. The model that includes as predictors all independent variables, all quadratic terms, and all interaction terms (the full quadratic model)."
