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

Question

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

Quizplus · Accepted Answer

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

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

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