OLS Regression Results ================================================================================= Dep. Variable: number O(n+1)-replies R-squared: 0.253 Model: OLS Adj. R-squared: 0.253 Method: Least Squares F-statistic: 9.746e+04 Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00 Time: 09:31:48 Log-Likelihood: -1.0810e+06 No. Observations: 575190 AIC: 2.162e+06 Df Residuals: 575187 BIC: 2.162e+06 Df Model: 2 Covariance Type: nonrobust ==================================================================================================== coef std err t P>|t| [0.025 0.975] ---------------------------------------------------------------------------------------------------- const 1.6458 0.002 787.663 0.000 1.642 1.650 bayes-corrected (q=0.25) valence -0.3951 0.002 -184.289 0.000 -0.399 -0.391 totalvotes 0.7495 0.002 349.574 0.000 0.745 0.754 ============================================================================== Omnibus: 194870.309 Durbin-Watson: 1.765 Prob(Omnibus): 0.000 Jarque-Bera (JB): 1100608.449 Skew: 1.527 Prob(JB): 0.00 Kurtosis: 9.050 Cond. No. 1.26 ============================================================================== Notes: [1] Standard Errors assume that the covariance matrix of the errors is correctly specified.