Ugh, multicollinearity is the bane of every regression analyst's existence. But C is the right call - those overly friendly predictors are the culprit.
I'm going with C. High correlation between explanatory variables is the textbook definition of multicollinearity. The other options just don't fit the bill.
Haha, I bet the exam writer is trying to trick us with those other options. But C is the clear winner here - multicollinearity is all about those pesky predictor variables getting too cozy with each other.
Elmira
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