OLS Regression Results ================================================================================= Dep. Variable: number O(n+1)-replies R-squared: 0.257 Model: OLS Adj. R-squared: 0.257 Method: Least Squares F-statistic: 8576. Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00 Time: 09:31:48 Log-Likelihood: -86794. No. Observations: 49462 AIC: 1.736e+05 Df Residuals: 49459 BIC: 1.736e+05 Df Model: 2 Covariance Type: nonrobust ==================================================================================================== coef std err t P>|t| [0.025 0.975] ---------------------------------------------------------------------------------------------------- const 1.3371 0.006 212.544 0.000 1.325 1.349 bayes-corrected (q=0.25) valence -0.4685 0.006 -73.917 0.000 -0.481 -0.456 totalvotes 0.6228 0.006 98.259 0.000 0.610 0.635 ============================================================================== Omnibus: 17663.533 Durbin-Watson: 1.771 Prob(Omnibus): 0.000 Jarque-Bera (JB): 106942.347 Skew: 1.595 Prob(JB): 0.00 Kurtosis: 9.459 Cond. No. 1.13 ============================================================================== Notes: [1] Standard Errors assume that the covariance matrix of the errors is correctly specified.