For the regression model Yi = B₁ + B₂x₁2 + B3X i3 + Ci what happens if xi3 = 2x₁2 + 3 for all ?? Select one: The statistical inference becomes invalide due to non-normality b. The least-squares estimators are best with the smallest possible variance O c. The regression is not estimable because of exact collinearity d. The least-squares estimators are unbiased a.
For the regression model Yi = B₁ + B₂x₁2 + B3X i3 + Ci what happens if xi3 = 2x₁2 + 3 for all ?? Select one: The statistical inference becomes invalide due to non-normality b. The least-squares estimators are best with the smallest possible variance O c. The regression is not estimable because of exact collinearity d. The least-squares estimators are unbiased a.
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
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Transcribed Image Text:For the regression model
Y₁ = B₁ + B₂x₁2 + B 3 x ₁3 + ei
Yi
what happens if xi3 = 2x2 + 3 for all ??
Select one:
a.
The statistical inference becomes invalide due to non-normality
b.
The least-squares estimators are best with the smallest possible variance
O C.
The regression is not estimable because of exact collinearity
d. The least-squares estimators are unbiased
Expert Solution
Step 1
The regression model is given by,
yi=β1+β2xi2+β3xi3+ei
If xi3=2xi2+3 then the regression equation becomes:
yi=β1+β2xi2+β3(2xi2+3)+ei
or, yi=(β1+3β3)+(β2+2β3)xi2+ei
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