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How to Interpret Stata

# How to Interpret Stata - Interpreting Stata Results to...

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Interpreting Stata Results - 1 Interpreting Stata Results to accompany the textbook : R. Carter Hill, William E. Griffiths and Guay C. Lim, Principles of Econometrics . Chapters 2 to 4 introduce the simple linear regression model with application to the estimation and analysis of the food expenditure function. Stata estimation results are: . regress food_exp income Source | SS df MS Number of obs = 40 -------------+------------------------------ F( 1, 38) = 23.79 Model | 190626.98 1 190626.98 Prob > F = 0.0000 Residual | 304505.173 38 8013.29403 R-squared = 0.3850 -------------+------------------------------ Adj R-squared = 0.3688 Total | 495132.153 39 12695.6962 Root MSE = 89.517 ------------------------------------------------------------------------------ food_exp | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- income | 10.20964 2.093263 4.88 0.000 5.972052 14.44723 _cons | 83.41601 43.41016 1.92 0.062 -4.463272 171.2953 . estat vce Covariance matrix of coefficients of regress model e(V) | income _cons -------------+------------------------ income | 4.381752 _cons | -85.903153 1884.4422 This handout matches the Stata results to the textbook presentation of the linear regression model.

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Interpreting Stata Results - 2 Analysis of Variance Table Source SS Sum of Squares df MS Mean Square Model SSR K - 1 SSR/( K - 1) Residual SSE N - K 2 ˆ SSE K N 1 σ = - Total SST N - 1 2 y s SST 1 N 1 = - K is the number of estimated coefficients. For the simple linear regression model K = 2.
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