Question: OLS Regression Results Dep. Variable: mpg R-squared: 0. 831 Model : OLS Adj. R-squared: 0 . 818 Method : Least Squares F-statistic: 66.35 Date :


OLS Regression Results Dep. Variable: mpg R-squared: 0. 831 Model : OLS Adj. R-squared: 0 . 818 Method : Least Squares F-statistic: 66.35 Date : Thu, 09 Jun 2022 Prob (F-statistic ) : 3.79e-11 Time : 17 : 12 :34 Log-Likelihood: -67 . 021 No. Observations : 30 AIC : 140.0 Df Residuals : 27 BIC : 144.2 Df Model : 2 Covariance Type: nonrobust coef std err t P> t [0 . 025 0.975] Intercept 35 . 9638 1 . 540 23.346 0 . 000 32 . 803 39 . 125 wt -3. 7315 0. 599 -6 . 233 0 . 000 -4. 960 -2 . 503 hp -0 . 0282 0 . 009 -3. 242 0 . 003 -0 . 046 -0 . 010 Omnibus : 7. 721 Durbin-Watson : 1. 287 Prob ( Omnibus ) : 0 . 021 Jarque-Bera (JB) : 5. 987 Skew : 0. 984 Prob ( JB ) : 0 . 0501 Kurtosis : 3.957 Cond. No. 611. Warnings
Step by Step Solution
There are 3 Steps involved in it
Get step-by-step solutions from verified subject matter experts
