OLS Regression Results ================================================================================= Dep. Variable: number O(n+1)-replies R-squared: 0.196 Model: OLS Adj. R-squared: 0.196 Method: Least Squares F-statistic: 7.576e+04 Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00 Time: 09:31:48 Log-Likelihood: -1.0058e+06 No. Observations: 620776 AIC: 2.012e+06 Df Residuals: 620773 BIC: 2.012e+06 Df Model: 2 Covariance Type: nonrobust ==================================================================================================== coef std err t P>|t| [0.025 0.975] ---------------------------------------------------------------------------------------------------- const 1.1396 0.002 734.230 0.000 1.137 1.143 bayes-corrected (q=0.25) valence -0.3478 0.002 -223.518 0.000 -0.351 -0.345 totalvotes 0.4695 0.002 301.664 0.000 0.466 0.473 ============================================================================== Omnibus: 202475.900 Durbin-Watson: 1.799 Prob(Omnibus): 0.000 Jarque-Bera (JB): 1088427.374 Skew: 1.479 Prob(JB): 0.00 Kurtosis: 8.773 Cond. No. 1.08 ============================================================================== Notes: [1] Standard Errors assume that the covariance matrix of the errors is correctly specified.