Below is a print screen of a summary(lm(..)).
I called the response variable response explained by a continuous variable X and a factor Y.

I'm trying to understand (not to the point of understanding the algorithms used to compute these results) the meaning of this output. My questions might be duplicates, but I haven't found the answer anywhere or if I did, I couldn't understand it!
The model is
response = -4.461010 + blabla... What does the p.value for this intercept mean? Does it mean that the predicted line of my data significantly does not pass by the Origin?factor(Y)2is significant. Does it mean that for the subset ofdata2whereYequals 2, the values ofresponseare significantly different than in the subset whereYequals 1 (which is taken as a reference)?Imagine a graph where the lines for
subset(data2,Y==1)andsubset(data2,Y==2)look alike but the line forsubset(data2,Y==3)is totally different. Iffactor(Y)3is taken as a reference, we'll get the two others to be significant and iffactor(Y)1is taken as a reference,factor(Y)3will be significant but notfactor(Y)2. Is it correct?For the interactions
X:Y2andX:Y3. Does the low p.values mean that for both the subsetY==2andY==3, the variableXacts differently than it does for the subsetY==1?
Thanks a lot for your help!
anova(lm(..)). – user12719 Aug 30 '13 at 16:44anovafunction. I think I understand the results of the anova. I just don't understand the output of thesummary(lm(..)). Do my above questions make sense? It is really the meaning of each line in the output example that interests me. – Remi.b Aug 30 '13 at 17:37polyis explained at http://stats.stackexchange.com/questions/66280. The interpretation of interactions is explained in many threads: do a search. Interpreting regression coefficients is explained in many threads; this one also explains the p-values andR's output: http://stats.stackexchange.com/questions/5135. – whuber Aug 30 '13 at 18:08