Which LSRL is a better fit?

The computer output from a set of data and a transformed set of data are below. Regression 1: Coefficients Standard Error t Stat P-value Intercept0.0143604670.034141675 0.4206140030.688685733 vim; 1.418734011 0.004125148 343.9231716 4.07828E-14 R-sq. = 99.9% Rsq.(adj) = 99.9% Regression 2: Coefficients Standard Error t Stat P-value Intercept101.415925917.93387419 5.6549926050.001312963 Area 30.83592593 2.166849924 14.23076217 7.52727E-D6 R-sq. = 97.1% Rsq.(adj) = 95.5% Which LSRL is a better t? Explain. (4 points) A Regression 2 is a better t because the intercept is positive. A Regression 2 is a better t because r-squared is farther from 1 than rsquared in regression 1. A Unable to determine which is a better t. A Regression 1 is a better t because r-squared is closer to 1 than r-squared in regression 2. A Regression 1 is a better t because the intercept is closer to zero than the intercept in regression 2