# CLRM – Assumption 1: Linear Parameter and correct model specification

Assumption 1 requires that the dependent variable $\textbf{y}$ is a linear combination of the explanatory variables $\textbf{X}$ and the error terms $\epsilon$. Assumption 1 requires the specified model to be linear in parameters, but it does not require the model to be linear in variables. Equation 1 and 2 depict a model which is both, linear in parameter and variables. Note that Equation 1 and 2 show the same model in different notation.