Linear Regression Model
Y ~ X
coefficients:
	Estimate	Std. Error	t value	Pr(>|t|)
(Intercept)	-39.622	86.341	-0.459	0.649
X	2.113	0.868	2.435	0.02
- - -
Residual Std. Err.	72.27 on 33 df
Multiple R-sq.	0.152
Adjusted R-sq.	0.127

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
weightbase	1	30971.65	30971.65	5.93	0.02
Residuals	33	172357.093	5222.942