OLS Regression Results ================================================================================= Dep. Variable: number O(n+1)-replies R-squared: 0.256 Model: OLS Adj. R-squared: 0.256 Method: Least Squares F-statistic: 2.267e+04 Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00 Time: 09:31:48 Log-Likelihood: -2.1421e+05 No. Observations: 131977 AIC: 4.284e+05 Df Residuals: 131974 BIC: 4.284e+05 Df Model: 2 Covariance Type: nonrobust ==================================================================================================== coef std err t P>|t| [0.025 0.975] ---------------------------------------------------------------------------------------------------- const 1.0804 0.003 320.014 0.000 1.074 1.087 bayes-corrected (q=0.25) valence -0.4040 0.003 -118.355 0.000 -0.411 -0.397 totalvotes 0.5375 0.003 157.450 0.000 0.531 0.544 ============================================================================== Omnibus: 54168.298 Durbin-Watson: 1.825 Prob(Omnibus): 0.000 Jarque-Bera (JB): 590918.640 Skew: 1.674 Prob(JB): 0.00 Kurtosis: 12.811 Cond. No. 1.16 ============================================================================== Notes: [1] Standard Errors assume that the covariance matrix of the errors is correctly specified.