Question: Regression Statistics Multiple R 0.70995212 R Square 0.50403202 Adjusted R Square 0.50086627 Standard Error 12063.8519 Observations 474 ANOVA df SS MS F Significance F Regression
| Regression Statistics | ||||||||
| Multiple R | 0.70995212 | |||||||
| R Square | 0.50403202 | |||||||
| Adjusted R Square | 0.50086627 | |||||||
| Standard Error | 12063.8519 | |||||||
| Observations | 474 | |||||||
| ANOVA | ||||||||
| df | SS | MS | F | Significance F | ||||
| Regression | 3 | 6.9514E+10 | 2.3171E+10 | 159.21394 | 3.3298E-71 | |||
| Residual | 470 | 6.8402E+10 | 145536523 | |||||
| Total | 473 | 1.3792E+11 | ||||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
| Intercept | -13313.269 | 2763.35782 | -4.8177869 | 1.9618E-06 | -18743.334 | -7883.2043 | -18743.334 | -7883.2043 |
| gender | 9022.21202 | 1201.22739 | 7.51082778 | 2.9827E-13 | 6661.77117 | 11382.6529 | 6661.77117 | 11382.6529 |
| minority | -5116.84 | 1362.97752 | -3.7541631 | 0.00019571 | -7795.1237 | -2438.5562 | -7795.1237 | -2438.5562 |
| education | 3257.19864 | 208.853422 | 15.5956201 | 1.708E-44 | 2846.79661 | 3667.60066 | 2846.79661 | 3667.60066 |
- A measure on how well the independent variables gender, minority, and education are able to explain the variation in average salary is the adjusted R Squared. What percentage of the variation in average salaries is described by these variables?
- The t Stat is a measure of how an individual independent variable explains variation in the dependent variable average salary. An absolute value greater than 2 is generally considered a significant value in explaining variation. What do the t Stats tell us about the ability of the variables gender, minority, and education to explain average salary?
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