OLS Regression Results Dep. Variable: Model: Method: Date: Time: No. Observations: Df Residuals: Df Model: Covariance Ty

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Ols Regression Results Dep Variable Model Method Date Time No Observations Df Residuals Df Model Covariance Ty 1 (643.75 KiB) Viewed 54 times

OLS Regression Results Dep. Variable: Model: Method: Date: Time: No. Observations: Df Residuals: Df Model: Covariance Type: mpg OLS Least Squares Wed, 17 Jan 2018 14:07:51 32 30 1 nonrobust R-squared: Adj. R-squared: F-statistic: Prob (F-statistic): Log-Likelihood: AIC: BIC: 0.360 0.338 16.86 0.000285 -95.242 194.5 197.4 ==== coef std err t P>It [0.025 0.975] constant am 17.1474 7.2449 1.125 1.764 15.247 4.106 0.000 0.000 14.851 3.642 19.444 10.848 Omnibus: Prob nibus): Skew: Kurtosis: 0.480 0.787 0.051 2.343 Durbin-Watson: Jarque-Berd JB): Prob(JB): Cond. No. 1.065 0.589 0.745 2.46 == Assuming x and y are in logs, compute the average marginal effect considering that ymean=10 and xmean=5 0.725 14.50 36 7.25