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True/False Explain. Even if one of the first four multiple regression assumptions is violated (i.e., any of correct model, correct sample, no perfect collinearity, no

True/False Explain.

Even if one of the first four multiple regression assumptions is violated (i.e., any of correct model, correct sample, no perfect collinearity, no correlation between x and u), the estimates of the standard errors are still unbiased as long as the errors are homoskedastic.

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