Non-linear relationships have an apparent pattern, just not linear. For example, as age increases height increases up to a point then levels off after reaching a maximum height.

When you have one independent variable, it's easy to see the curvature using a fitted line plot. However, with multiple regression, curved relationships are not always so apparent. For these cases,residual plots are a key indicator for whether your model adequately captures curved relationships.

If you see a pattern in the residual plots, your model doesn't provide an adequate fit for the data. A common reason is that your model incorrectly models the curvature. Plotting theresidualsby each of yourindependent variablescan help you locate the curved relationship.

What happens if you apply linear regression in this case? Is there an alternative approach that you can use in this scenario? What is meant by standard error of estimate and how is it used to estimate the accuracy of prediction using the regression equation? Include references as well