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5. (02.05 LC)
Prior to fitting a linear regression model with x and y variables, both variables were transformed using logarithms. The following computer output was produced.

Coefficients Standard Error t Stat P-value
Intercept 5.672 1.483 22.98 0.0002
Log (x) −2.583 0.037 −7.56 0.0003

R-sq. = 82.14% R-sq.(adj) = 81.25%

Part A: Interpret the value of r2. (5 points)
Part B: Assuming the residual plot of the transformed data shows a pattern, comment on the appropriateness of this linear regression for modeling the relationship between the transformed variables. (5 points)

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5. (02.05 LC)
Prior to fitting a linear regression model with x and y variables, both variabl...
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