Prior to fitting a linear regression model with x and y variables, the y variable was transformed by performing a cube root. The following computer output was produced. CoefficientsStandard Errort StatP-value

Intercept 3.482 2.467 23.840.0021

x-variable −2.783 0.024 −8.370.0013

R-sq. = 80.34%R-sq.(adj) = 82.56%

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.