OLS Regression Results ============================================================================== Dep. Variable: np.log10(newborn) R-squared: 0.948 Model: OLS Adj. R-squared: 0.948 Method: Least Squares F-statistic: 1.478e+04 Date: Mon, 29 Jun 2015 Prob (F-statistic): 0.00 Time: 16:15:21 Log-Likelihood: -215.62 No. Observations: 816 AIC: 435.2 Df Residuals: 814 BIC: 444.7 Df Model: 1 Covariance Type: nonrobust ================================================================================== coef std err t P>|t| [95.0% Conf. Int.] ---------------------------------------------------------------------------------- Intercept -1.1394 0.027 -42.018 0.000 -1.193 -1.086 np.log10(mass) 0.9496 0.008 121.567 0.000 0.934 0.965 ============================================================================== Omnibus: 100.291 Durbin-Watson: 0.808 Prob(Omnibus): 0.000 Jarque-Bera (JB): 167.930 Skew: -0.800 Prob(JB): 3.42e-37 Kurtosis: 4.542 Cond. No. 9.12 ============================================================================== Warnings: [1] Standard Errors assume that the covariance matrix of the errors is correctly specified.