Linear Regression Model
Y ~ X
coefficients:
	Estimate	Std. Error	t value	Pr(>|t|)
(Intercept)	3.812	0.363	10.511	0
X	0.084	0.079	1.066	0.288
- - -
Residual Std. Err.	0.635 on 162 df
Multiple R-sq.	0.007
95% CI Multiple R-sq.	[0, 0.059]
Adjusted R-sq.	0.001

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
UTD	1	0.458	0.458	1.136	0.288
Residuals	162	65.298	0.403