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OLS_result.txt
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OLS Regression Results
=======================================================================================
Dep. Variable: rating R-squared (uncentered): 0.979
Model: OLS Adj. R-squared (uncentered): 0.979
Method: Least Squares F-statistic: 1.876e+04
Date: Sun, 31 Jul 2022 Prob (F-statistic): 0.00
Time: 04:34:21 Log-Likelihood: -3768.6
No. Observations: 2784 AIC: 7551.
Df Residuals: 2777 BIC: 7593.
Df Model: 7
Covariance Type: nonrobust
=================================================================================
coef std err t P>|t| [0.025 0.975]
---------------------------------------------------------------------------------
fbPosters -0.0420 0.009 -4.642 0.000 -0.060 -0.024
year 0.0022 4.82e-05 45.985 0.000 0.002 0.002
duration 0.0135 0.001 15.562 0.000 0.012 0.015
contentRating 0.1200 0.010 12.122 0.000 0.101 0.139
criticReviews 0.0013 0.000 6.710 0.000 0.001 0.002
userReviews -0.0005 7.65e-05 -6.727 0.000 -0.001 -0.000
userVotes 3.248e-06 2.17e-07 14.940 0.000 2.82e-06 3.67e-06
==============================================================================
Omnibus: 350.876 Durbin-Watson: 2.006
Prob(Omnibus): 0.000 Jarque-Bera (JB): 632.304
Skew: -0.822 Prob(JB): 4.98e-138
Kurtosis: 4.658 Cond. No. 9.42e+04
==============================================================================
Notes:
[1] R² is computed without centering (uncentered) since the model does not contain a constant.
[2] Standard Errors assume that the covariance matrix of the errors is correctly specified.
[3] The condition number is large, 9.42e+04. This might indicate that there are
strong multicollinearity or other numerical problems.