I have generated a summary for a particular multiple linear regression
> mod1 <- lm(log(wage) ~ education + experience + age)
> summary(mod1)
Call:
lm(formula = log(wage) ~ education + experience + age)
Residuals:
Min 1Q Median 3Q Max
-2.03367 -0.33094 0.04165 0.31958 1.84066
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.84480 0.71884 1.175 0.240
education 0.13805 0.11791 1.171 0.242
experience 0.05353 0.11796 0.454 0.650
age -0.04173 0.11786 -0.354 0.723
Residual standard error: 0.4699 on 530 degrees of freedom
Multiple R-squared: 0.2117, Adjusted R-squared: 0.2072
F-statistic: 47.44 on 3 and 530 DF, p-value: < 2.2e-16
Since the F-statistic = 47.44 is larger than the cut-off value qf(0.95, 3, 530) = 2.622, I can reject the null hypothesis that states the model is not significant. But on the other hand, I find that the p-values are larger than 0.05. What is the reason for this? Is there a way to solve this?
