Evaluate the following statement: \"For the least squares method to be fully val

Question

Evaluate the following statement: "For the least squares method to be fully valid, it is required that the distribution of Y be normal."

I'm not sure about this. Since i is assumed a normal random variable and X is an independent variable, then I would think Y as the response variable must be normally distributed. On the other hand, the least squares method "minimizes the sum of the squares of the residuals made in the results of every single equation", so in theory, you could have a different form from the common least squares method that has a non-linear form, them I think you could have a non-linear distributed Y. Also nowhere in my textbook states it has to be normally distributed.

Explanation / Answer

The statement,"For the least squares method to be fully valid, it is required that the distribution of Y be normal" is not correct.

EXPLANATION: The least square method makes no assumption about the normality condition of the distribution of the independent variable in regression model.Only the errors follow a Normal Distribution.

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