Below is a print screen of a summary(lm(..)).
I called the response variable
response explained by a continuous variable
X and a factor
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 of
Yequals 2, the values of
responseare significantly different than in the subset where
Yequals 1 (which is taken as a reference)?
Imagine a graph where the lines for
subset(data2,Y==2)look alike but the line for
subset(data2,Y==3)is totally different. If
factor(Y)3is taken as a reference, we'll get the two others to be significant and if
factor(Y)1is taken as a reference,
factor(Y)3will be significant but not
factor(Y)2. Is it correct?
For the interactions
X:Y3. Does the low p.values mean that for both the subset
Y==3, the variable
Xacts differently than it does for the subset
Thanks a lot for your help!