If when using the model $E ( y ) = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \beta _ { 3 } x _ { 1 } x _ { 2 }$ we determine that interaction between $x _ { 1 }$ and $x _ { 2 }$ is not significant, we can drop the $x _ { 1 } x _ { 2 }$ term from the model and use the simpler model $E ( y ) = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 }$.

Question

Quizplus · Accepted Answer

If the interaction term $x_1 x_2$ is found to be not significant, it indicates that the interaction between $x_1$ and $x_2$ does not significantly contribute to explaining the variation in $y$. Therefore, the model can be simplified by removing this term, leading to a simpler model without significantly reducing its explanatory power.

If When Using the Model E(y)=β0+β1x1+β2x2+β3x1x2E ( y ) = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \beta _ { 3 } x _ { 1 } x _ { 2 }E(y)=β0​+β1​x1​+β2​x2​+β3​x1​x2​

If When Using the Model $E ( y ) = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \beta _ { 3 } x _ { 1 } x _ { 2 }$