# 4: Multi-factor Regression


A multi-factor regression model is a generalization of the simple one- factor regression model discussed in Chapter 3. It has n factors with the form:

y = a0 + a1x1 + a2x2 + ...anxn,

where the xi values are the inputs to the system, the ai coefficients are the model parameters computed from the measured data, and y is the output value predicted by the model. Everything we learned in Chapter 3 for one- factor models also applies to the multi-factor models. To develop this type of multi-factor regression model, we must also learn how to select specific predictors to include in the model

4: Multi-factor Regression is shared under a CC BY-NC 4.0 license and was authored, remixed, and/or curated by David Lilja via source content that was edited to conform to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.