Part 3: Interpretation of OLS regression Consider the following OLS regression output which is estimated with Wage2.dta (see tutorial folder on Blackboard) Source ss df MS Number of obs 935 F (4, 930) 36.82 Model 22.6467366 4 5.66168416 Prob > F 0.0000 Residual 143.009547 930 .153773706 R-squared Adj R-squared 0.1367 0.1330 Total 165.656283 934 .177362188 Root MSE .39214 lwage Coef. Std. Err. t P>|t| [95% Conf. Interval] educ .0400982 .0068351 5.87 0.000 .0266843 .0535122 IO .005914 0009967 5.93 0.000 .0039579 .0078701 I|||| I
Part 3: Interpretation of OLS regression Consider the following OLS regression output which is estimated with Wage2.dta (see tutorial folder on Blackboard) Source ss df MS Number of obs 935 F (4, 930) 36.82 Model 22.6467366 4 5.66168416 Prob > F 0.0000 Residual 143.009547 930 .153773706 R-squared Adj R-squared 0.1367 0.1330 Total 165.656283 934 .177362188 Root MSE .39214 lwage Coef. Std. Err. t P>|t| [95% Conf. Interval] educ .0400982 .0068351 5.87 0.000 .0266843 .0535122 IO .005914 0009967 5.93 0.000 .0039579 .0078701 I|||| I
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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