You’ve run a regression of the effect of years of schooling on wages for a sample of 102,498 individuals. Your regression results are: wage = 2.051 + 0.29 × Years of Schooling (0.0802) (0.0168) Interpret the coefficients from this regression. (The coefficients are shown in the regression equation itself.) The numbers in parentheses under the equation are the standard errors of the estimates for the respective coefficients. Determine whether each coefficient is statistically significant at each of the conventional significance levels. The R2 for this regression is 0.284. Interpret the meaning of this value.
You’ve run a regression of the effect of years of schooling on wages for a sample of 102,498 individuals. Your regression results are: wage = 2.051 + 0.29 × Years of Schooling (0.0802) (0.0168) Interpret the coefficients from this regression. (The coefficients are shown in the regression equation itself.) The numbers in parentheses under the equation are the standard errors of the estimates for the respective coefficients. Determine whether each coefficient is statistically significant at each of the conventional significance levels. The R2 for this regression is 0.284. Interpret the meaning of this value.
Chapter4: Linear Functions
Section: Chapter Questions
Problem 41RE: For the following exercises, consider the data in Table 5, which shows the percent of unemployed in...
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- You’ve run a regression of the effect of years of schooling on wages for a sample of 102,498 individuals. Your regression results are:
wage = 2.051 + 0.29 × Years of Schooling
(0.0802) (0.0168)
- Interpret the coefficients from this regression. (The coefficients are shown in the regression equation itself.)
- The numbers in parentheses under the equation are the standard errors of the estimates for the respective coefficients. Determine whether each coefficient is statistically significant at each of the conventional significance levels.
- The R2 for this regression is 0.284. Interpret the meaning of this value.
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