OLS Regression Results ================================================================================= Dep. Variable: number O(n+1)-replies R-squared: 0.220 Model: OLS Adj. R-squared: 0.220 Method: Least Squares F-statistic: 6.744e+05 Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00 Time: 09:31:43 Log-Likelihood: -8.1863e+06 No. Observations: 4786218 AIC: 1.637e+07 Df Residuals: 4786215 BIC: 1.637e+07 Df Model: 2 Covariance Type: nonrobust ==================================================================================================== coef std err t P>|t| [0.025 0.975] ---------------------------------------------------------------------------------------------------- const 1.1760 0.001 1922.382 0.000 1.175 1.177 bayes-corrected (q=0.25) valence -0.4349 0.001 -707.468 0.000 -0.436 -0.434 totalvotes 0.5207 0.001 847.067 0.000 0.520 0.522 ============================================================================== Omnibus: 2282674.662 Durbin-Watson: 1.758 Prob(Omnibus): 0.000 Jarque-Bera (JB): 64040137.713 Skew: 1.723 Prob(JB): 0.00 Kurtosis: 20.586 Cond. No. 1.10 ============================================================================== Notes: [1] Standard Errors assume that the covariance matrix of the errors is correctly specified.