Multicollinearity said in "plain English" is redundancy. Unfortunately, it isn't quite that simple, but it's a good place to start. Put simply, multicollinearity is when two or more predictors in a regression are highly related to one another, such that they do not provide unique and/or independent information to the regression.
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