OLS Regression Results ================================================================================= Dep. Variable: number O(n+1)-replies R-squared: 0.198 Model: OLS Adj. R-squared: 0.198 Method: Least Squares F-statistic: 1.449e+04 Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00 Time: 09:31:48 Log-Likelihood: -1.9705e+05 No. Observations: 117051 AIC: 3.941e+05 Df Residuals: 117048 BIC: 3.941e+05 Df Model: 2 Covariance Type: nonrobust ==================================================================================================== coef std err t P>|t| [0.025 0.975] ---------------------------------------------------------------------------------------------------- const 1.3476 0.004 353.887 0.000 1.340 1.355 bayes-corrected (q=0.25) valence -0.3144 0.004 -80.973 0.000 -0.322 -0.307 totalvotes 0.5090 0.004 131.111 0.000 0.501 0.517 ============================================================================== Omnibus: 32287.766 Durbin-Watson: 1.796 Prob(Omnibus): 0.000 Jarque-Bera (JB): 111823.546 Skew: 1.377 Prob(JB): 0.00 Kurtosis: 6.917 Cond. No. 1.22 ============================================================================== Notes: [1] Standard Errors assume that the covariance matrix of the errors is correctly specified.