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# Why the Enter Method is used in Multiple Regression

Explain why most researcher use the default(Enter) method for model building.

#### Solution Preview

To understand this, you need to understand the logic that underlies multiple regression. In multiple regression, we're trying to predict one variable (y) from a set of other variables (x1, x2, x3, etc). We decide whether each x variable should stay in the regression model by looking at how much variance in y each explains. Only variables that explain a lot of variance in y stay in the model.

Let's start simple. Imagine we're doing a simple regression, where we're trying to predict a variable (y) from a single variable (x). For example, if we were predicting 'years of schooling' from 'age', we would expect that age (x) would explain a lot of variance in years of schooling (y) (and would be a significant predictor in the model). In contrast, if we were predicting 'years of schooling' from 'hair colour', we would expect that hair colour (x) was not a good predictor of years of schooling (y): it would not explain a lot of variance in y (and would not be a significant ...

#### Solution Summary

Explains the theory underlying the use of the default Enter method in multiple regression analyses.

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