Suppose that the true relationship between y; and ; is as follows, Yi =B₁ + B₂x₁ + Uj The error term satisfies that E[ui] = 0 and Var(u) = 1. You find another variable zi whose sample correlation with ₂ is equal to -1. Select correct statement(s).
Suppose that the true relationship between y; and ; is as follows, Yi =B₁ + B₂x₁ + Uj The error term satisfies that E[ui] = 0 and Var(u) = 1. You find another variable zi whose sample correlation with ₂ is equal to -1. Select correct statement(s).
Chapter6: Exponential And Logarithmic Functions
Section6.8: Fitting Exponential Models To Data
Problem 3TI: Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to...
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![Suppose that the true relationship between y; and ; is as follows,
Yi = B₁ + B₂xi + Ui
The error term satisfies that E[u₂] = 0 and Var(u) = 1. You find
another variable zi whose sample correlation with x is equal to -1.
Select correct statement(s).
Because the correlation is equal to -1, we have %₁ = -₂.
O If we add z; in the regression model along with ;, R² will be increased.
Adding z; along with in the regression model is not plausible because
of the perfect multicollinearity.
O If we estimate the model y₁ = a₁ + a2%; + e₁, the estimator of a2 will
be equal to -3₂, where B₂ is the OLS estimator of 32](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F7afc2de4-22ca-41c7-9e00-d318df3d7e5d%2Fda8d6e22-ea4a-4544-a371-f973f4d0c0fc%2F26t3k1b_processed.png&w=3840&q=75)
Transcribed Image Text:Suppose that the true relationship between y; and ; is as follows,
Yi = B₁ + B₂xi + Ui
The error term satisfies that E[u₂] = 0 and Var(u) = 1. You find
another variable zi whose sample correlation with x is equal to -1.
Select correct statement(s).
Because the correlation is equal to -1, we have %₁ = -₂.
O If we add z; in the regression model along with ;, R² will be increased.
Adding z; along with in the regression model is not plausible because
of the perfect multicollinearity.
O If we estimate the model y₁ = a₁ + a2%; + e₁, the estimator of a2 will
be equal to -3₂, where B₂ is the OLS estimator of 32
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