OLS Regression Results ================================================================================= Dep. Variable: number O(n+1)-replies R-squared: 0.136 Model: OLS Adj. R-squared: 0.136 Method: Least Squares F-statistic: 3.982e+05 Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00 Time: 09:31:50 Log-Likelihood: -6.2998e+06 No. Observations: 5050120 AIC: 1.260e+07 Df Residuals: 5050117 BIC: 1.260e+07 Df Model: 2 Covariance Type: nonrobust ==================================================================================================== coef std err t P>|t| [0.025 0.975] ---------------------------------------------------------------------------------------------------- const 0.6133 0.000 1636.095 0.000 0.613 0.614 bayes-corrected (q=0.25) valence -0.2055 0.000 -548.027 0.000 -0.206 -0.205 totalvotes 0.2575 0.000 686.512 0.000 0.257 0.258 ============================================================================== Omnibus: 2832727.339 Durbin-Watson: 1.864 Prob(Omnibus): 0.000 Jarque-Bera (JB): 85433368.019 Skew: 2.153 Prob(JB): 0.00 Kurtosis: 22.684 Cond. No. 1.03 ============================================================================== Notes: [1] Standard Errors assume that the covariance matrix of the errors is correctly specified.