Linear Regression Model
Y ~ X
coefficients:
	Estimate	Std. Error	t value	Pr(>|t|)
(Intercept)	-4.165	10.037	-0.415	0.683
X	3.513	2.917	1.204	0.244
- - -
Residual Std. Err.	4.96 on 18 df
Multiple R-sq.	0.075
95% CI Multiple R-sq.	[0, 0.496]
Adjusted R-sq.	0.023

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
Gebgewicht	1	35.693	35.693	1.451	0.244
Residuals	18	442.857	24.603