Linear Regression Model
Y ~ X
coefficients:
	Estimate	Std. Error	t value	Pr(>|t|)
(Intercept)	-4.74	4.89	-0.969	0.348
X	1.007	0.047	21.277	0
- - -
Residual Std. Err.	2.93 on 15 df
Multiple R-sq.	0.968
Adjusted R-sq.	0.966

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
Weight-at-bassline	1	3886.713	3886.713	452.727	0
Residuals	15	128.777	8.585