To estimate the price of houses in $1000 in Boston, the following output is found. Is the model adequate for predicting the price of the house? OLS Regression Results Dep. Variable: price R-squared: 0.642 Model: OLS Adj. R-squared: 0.639 Method: Least Squares F-statistic: 224.5 Date: Wed, 17 Jul 2019 Prob (F-statistic): 3.01e-110 Time: 17:58:03 Log-Likelihood: -1580.4 No. Observations: 506 AIC: 3171. Of Residuals: 501 BIC: 3192. Df Model: Covariance Type: nonrobust coef std err [0.025 0.975] Intercept -0.3182 3.201 -0.099 0.921 -6.607 5.970 INDUS -0.1018 0.051 -2.012 0.045 -0.201 -0.002 RM 4.8889 0.458 10.685 0.000 3.990 5.788 AGE 0.0207 0.013 1.645 0.101 -0.004 0.045 LSTAT -0.6449 0.055 -11.629 0.000 -0.754 -0.536 Omnibus: 148.715 Durbin-Watson: 0.845 Prob(Omnibus): 0.000 Jarque-Bera (JB): 474.408 Skew: 1.366 Prob(JB): 9.63e-104 Kurtosis: 6.878 Cond. No. 1.01e+03 O The model is adequate as R*2 = 0.642. O The model is not adequate as R^2 = 0.642