Econometrics: Classical Assumption 1 – The model is linear in the slope coefficients and error term.

In this assumption, it is assumed that the model is linear in the slope coefficients and the associated error term in the equation. What this means is that the slope in a given linear equation is a number that it is neither squared or it is not a reciprocal for example. It is a number that once graphed within the context of the regression equation will ultimately produce a straight line. The same applies to the error term in this instance.

Always remember that a regression model only needs to be linear in the slope coefficients (parameters) to produce a straight line. Even if the associated variables are squared or cubed for example, as long as the slope coefficients are linear, the line of best fit will plot as a straight line.

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