OLS Regression Results ================================================================================= Dep. Variable: number O(n+1)-replies R-squared: 0.243 Model: OLS Adj. R-squared: 0.243 Method: Least Squares F-statistic: 3.781e+04 Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00 Time: 09:31:48 Log-Likelihood: -3.6290e+05 No. Observations: 235911 AIC: 7.258e+05 Df Residuals: 235908 BIC: 7.258e+05 Df Model: 2 Covariance Type: nonrobust ==================================================================================================== coef std err t P>|t| [0.025 0.975] ---------------------------------------------------------------------------------------------------- const 0.9173 0.002 395.396 0.000 0.913 0.922 bayes-corrected (q=0.25) valence -0.3334 0.002 -142.771 0.000 -0.338 -0.329 totalvotes 0.5075 0.002 217.346 0.000 0.503 0.512 ============================================================================== Omnibus: 99947.806 Durbin-Watson: 1.805 Prob(Omnibus): 0.000 Jarque-Bera (JB): 886847.368 Skew: 1.813 Prob(JB): 0.00 Kurtosis: 11.779 Cond. No. 1.12 ============================================================================== Notes: [1] Standard Errors assume that the covariance matrix of the errors is correctly specified.