could this equation suffer from omitted variable bias explain could this equatio
ID: 3354542 • Letter: C
Question
could this equation suffer from omitted variable bias explaincould this equation suffer from omitted variable bias explain
could this equation suffer from omitted variable bias explain
, regress gpa sat study hsgpa 60 41.98 0.0000 0.6922 Adj R-squared0.6757 4095 5S df MS Number of obs Source Model 21.1186423 Residual9.39065106 F(3, 56) 3 7.03954742 Prob > F 56 167690197R-squared Total 30. 5092933 59 517106667 Root MSE 9Pa Coef. Std. Err. t P>It! [95% conf. Interval] sat study 00121330003461 0268833 0 3.51e.0e1 00051990019067 8369869 0058037 5.370.000 0168596 hsgpa 3821342 .1197388 3.19 0.0021422686 6219998 .cons-582720738106491.530.132 1.346085 1806441
Explanation / Answer
1. No this equation wont suffer from omitted variable bias as it is a case of multiple linear regression and the equation will tell us any way how significant each independent variable is in predicting the dependent variable through the linear regression equation. It gives us the coefficient for each of the variables, their standard error and how significant they are in predicting for the population at the 95% Confidence Interval. Most of them have very low p values and hence are significant in predicting for the dependent variable. The R-Squared value or the coefficient of determination is at 0.6922, the linear fit of the model is very strong as it is quite close to one.
Hence the equation wont suffer from omiited variable bias.
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