# Interpretation of R's lm() output

the help pages in R assume I know what those numbers mean. I don't :) I'm trying to really intuitively understand every number here. I will just post the output and comment on what I found out. There might (will) be mistakes, as I'll just write what I assume. Please correct me, and I will edit the wrong parts.
Mainly I'd like to know what the t-value in the coefficients mean, and why they print the residual standard error. I hope someone can clarify that.

Call:
lm(formula = iris$Sepal.Width ~ iris$Petal.Width)

Residuals:
Min       1Q   Median       3Q      Max
-1.09907 -0.23626 -0.01064  0.23345  1.17532


A 5-point-summary of the residuals (Their mean is always 0, right?). The numbers can be used (I'm guessing here) to quickly see if there are any big outliers. Also you can already see it here if the residuals are far from normally distributed (they should be normally distributed).

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept)       3.30843    0.06210  53.278  < 2e-16 ***

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