When using the model $E ( y ) = \beta _ { 0 } + \beta _ { 1 } x$ for one qualitative independent variable with a $0 - 1$ coding convention, $\beta _ { 1 }$ represents the difference between the mean responses for the level assigned the value 1 and the base level.

Question

Quizplus · Accepted Answer

In a model with a binary qualitative independent variable coded as 0 and 1, $\beta_1$ represents the change in the mean response when the variable changes from the base level (0) to the level assigned the value 1.

When Using the Model E(y)=β0+β1xE ( y ) = \beta _ { 0 } + \beta _ { 1 } xE(y)=β0​+β1​x

When Using the Model $E ( y ) = \beta _ { 0 } + \beta _ { 1 } x$