Models associated with regression and classification data approaches have all have these important parts except.

Multiple Choice

identifying which variables $($we$\text{'}$ll call these independent variables$)$ might help predict an outcome $($we$\text{'}$ll call this the

dependent variable$).$

the functional form of the relationship $($linear$,$ nonlinear, etc.$).$

the numeric parameters of the model $($detailing the relative weights of each of the variables associated with the prediction$).$