Linear Regression Model
Y ~ X
coefficients:
	Estimate	Std. Error	t value	Pr(>|t|)
(Intercept)	3.695	0.33	11.185	0
X	0.032	0.02	1.594	0.113
- - -
Residual Std. Err.	0.625 on 160 df
Multiple R-sq.	0.016
95% CI Multiple R-sq.	[0, 0.082]
Adjusted R-sq.	0.009

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
ITHSUM	1	0.991	0.991	2.54	0.113
Residuals	160	62.447	0.39