OLS Regression Results ================================================================================= Dep. Variable: number O(n+1)-replies R-squared: 0.237 Model: OLS Adj. R-squared: 0.237 Method: Least Squares F-statistic: 1.380e+05 Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00 Time: 09:31:48 Log-Likelihood: -1.5539e+06 No. Observations: 890221 AIC: 3.108e+06 Df Residuals: 890218 BIC: 3.108e+06 Df Model: 2 Covariance Type: nonrobust ==================================================================================================== coef std err t P>|t| [0.025 0.975] ---------------------------------------------------------------------------------------------------- const 1.1789 0.001 802.397 0.000 1.176 1.182 bayes-corrected (q=0.25) valence -0.4979 0.001 -337.303 0.000 -0.501 -0.495 totalvotes 0.5435 0.001 368.179 0.000 0.541 0.546 ============================================================================== Omnibus: 415616.007 Durbin-Watson: 1.775 Prob(Omnibus): 0.000 Jarque-Bera (JB): 8567668.092 Skew: 1.765 Prob(JB): 0.00 Kurtosis: 17.782 Cond. No. 1.10 ============================================================================== Notes: [1] Standard Errors assume that the covariance matrix of the errors is correctly specified.