**by Jeff Meyer**

In a simple linear regression model, how the constant (a.k.a., intercept) is interpreted depends upon the type of predictor (independent) variable.

If the predictor is categorical and dummy-coded, the constant is the mean value of the outcome variable for the reference category only. If the predictor variable is continuous, the constant equals the predicted value of the outcome variable when the predictor variable equals zero.

**Removing the Constant When the Predictor Is Categorical**

When your predictor variable X is categorical, the results are logical. Let’s look at an example. [Read more…] about The Impact of Removing the Constant from a Regression Model: The Categorical Case