OLS Statsmodels Summary Table Explanation in details | Linear Regression Machine Learning|Data Scien

Here I explained the Stats-model summary Table statistics in details. Introduction 0:00 0:00 How to apply StatsModel OLS Linear Regression? 2:16 What is statsmodel.summary 3:33 DF(Degree of Freedom) residual 4:15 DF(Degree of freedom) Model 4:31 Covariance Type 6:10 R-Squared 6:03 Adjusted R-Squared 8:24 F-Statistics 11:24 Probability of F-Statistics 12:22 Log-Likelihood 15:05 AIC and BIC 17:57 Coefficient 19:02 Standard Error 21:16 Standard Error of Coefficient 22:51 t-statistics and P-Value of t-statistics 25:30 Omnibus and Probability of Omnibus -To test the residuals normal distribution 27:09 Skewness 27:53 Kurtosis 28:43 Durbin-Watson - Test the Auto-correlation in residuals 32:29 Jarque-Bera(JB) and Probability of Jarque-Bera(JB) -To test the residuals normal distribution 34:18 Condition Number To test the Multi-collinearity StatsModel OLS Video Link : https://youtu.be/vDgUtsGwZ0Y #AtulPatel #MachineLearning #LinearRegression #StatsModel Used Notebook in Video Link : https://github.com/atulpatelDS/Youtube/blob/main/Machine_Learning/Linear_Regression/Interpretaion_Model_Summary_statsmodels_Linear_Regression.ipynb