Question: Consider the simple linear regression model y i = 0 + 1x i + i , where the variance of i is proportional to xi

Consider the simple linear regression model y i = β0 + β1x i + εi , where the variance of εi is proportional to xi 2

, that is, Var( ) ε σ i i = x2 2.

a. Suppose that we use the transformations y′ = y / x and x′ = l/ x . Is this a variance - stabilizing transformation?

b. What are the relationships between the parameters in the original and transformed models?

c. Suppose we use the method of weighted least squares with w x i i = 1 2

. Is this equivalent to the transformation introduced in part a?

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