What are your conclusions from the full regression output displayed below:
summary(lm(sprint.speed ~ ., data = speed[, -1]))
Call:
lm(formula = sprint.speed ~ ., data = speed[, -1])
Residuals:
Min 1Q Median 3Q Max
-30.822 -10.580 2.242 8.097 49.890
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 32.95153 7.54762 4.366 7.57e-05 ***
body.mass -0.01256 0.00954 -1.316 0.195
hind.length 0.12220 0.13139 0.930 0.357
MT.F.ratio 45.15603 13.64308 3.310 0.002 **
c1adeHerbivore -14.44749 8.87279 -1.628 0.111
---
Residual standard error: 16.51 on 44 degrees of freedom
Multiple R-squared: 0.3781, Adjusted R-squared: 0.3215
F-statistic: 6.687 on 4 and 44 DF, p-value: 0.0002702