OLS Regression Results ================================================================================= Dep. Variable: number O(n+1)-replies R-squared: 0.246 Model: OLS Adj. R-squared: 0.246 Method: Least Squares F-statistic: 7.921e+04 Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00 Time: 09:31:48 Log-Likelihood: -8.1045e+05 No. Observations: 485006 AIC: 1.621e+06 Df Residuals: 485003 BIC: 1.621e+06 Df Model: 2 Covariance Type: nonrobust ==================================================================================================== coef std err t P>|t| [0.025 0.975] ---------------------------------------------------------------------------------------------------- const 1.1141 0.002 602.981 0.000 1.110 1.118 bayes-corrected (q=0.25) valence -0.4406 0.002 -237.533 0.000 -0.444 -0.437 totalvotes 0.5508 0.002 296.904 0.000 0.547 0.554 ============================================================================== Omnibus: 308614.044 Durbin-Watson: 1.795 Prob(Omnibus): 0.000 Jarque-Bera (JB): 33388300.741 Skew: 2.187 Prob(JB): 0.00 Kurtosis: 43.411 Cond. No. 1.09 ============================================================================== Notes: [1] Standard Errors assume that the covariance matrix of the errors is correctly specified.