Variance, Covariance Matrix, Linear Regression, Standard Error, Confidence Interval.
'City_MPG ~ Curb_Weight + Engine_Size' #Carve out the X and y matrices using Patsy y_train, X_train = dmatrices(model_expr, df_sample, return_type='dataframe') #Build an OLS regression model using Statsmodels olsr_model = sm.OLS(endog=y_train, exog=X_train) #Fit the model on (y, X) olsr_results =