Imagine a regression with one dependent variable (y) and two explanatory variables (x1 and x2).
Both coefficients of x1 and x2 are significant. But the intercept is around 0.1 is not significant. How to interpret this situation? The intercept must be y when both x1 and x2 = 0. If it is insignificant, it must mean that it can be concluded, at a certain significance level, that it is different from 0?
Imagine I add another variable to my model (x3). Now, the intercept changes to lets say 5 and becomes significant. What is going on here? How can x3 alter the intercept so much?