# Checking linearity assumption and colinearity assumption

Linear regression is equivalent to ANOVA. Do we need to check for linearity and multicolinearity for ANOVA? I have seen that these assumptions are usually omitted for ANOVA but not for linear regression. Please advise.

With ANOVA your explanatory/independent/right-hand-side/x-variables are typically categorical, so the linearity assumptions is automaticallly met. Say we have a continuous $x$-varialbe years of education, then we compare the expected $y$ for someone with 0 years of education with 1 year of education, 1 year of education with 2 years of education, 2 years of education with 3 years of education, etc. The linearity assumption says the difference in expected $y$ for each of these steps is the same. With a categorical explanatory variable, e.g. type of diploma, we don't make that assumption: we just compare someone with secondary education with someone with primary education, and someone with tertiary education with someone with primary education.