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 Errort 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.

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.