Question
Consider the following regression results:
Call:
lm(formula = y ~ x, data = d)
Residuals:
     Min       1Q   Median       3Q      Max 
-2.14867 -0.82868 -0.07472  0.66596  2.54119 
Coefficients:
             Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.0001676  0.1254992   0.001    0.999
x           1.2492437  0.1241613  10.061 2.04e-14
Residual standard error: 0.9786 on 59 degrees of freedom
Multiple R-squared:  0.6318,	Adjusted R-squared:  0.6255 
F-statistic: 101.2 on 1 and 59 DF,  p-value: 2.043e-14
Describe how the response y depends on the regressor x.
Solution
The presented results describe a linear regression.
The mean of the response y increases with increasing x.
If x increases by  unit then a change of y by about  units can be expected.
Also, the effect of x is  significant at the  percent level.