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Your Textbook Only Analyzed the Case of an Error-In-Variables Bias Xi~=Xi+wi\widetilde { X _ { i } } = X _ { i } + w _ { i }

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Your textbook only analyzed the case of an error-in-variables bias of the type Xi~=Xi+wi\widetilde { X _ { i } } = X _ { i } + w _ { i }
What if the error were generated in the simple regression model by entering data that always contained the same typographical error, say X~i=Xi+a or X~i=bXi\widetilde { X } _ { i } = X _ { i } + a \text { or } \widetilde { X } _ { i } = b X _ { i } where a and b are constants. What effect would this have on your regression model?

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