This is a similar question to Intercept significant but not the variables in GLM, but in more detail: my model's dependent variable is change in population density of a state, and the independent variables are various factors that may influence it (i.e. increased access to railways), along with one dummy (categorical) independent variable (if the state borders a coast or not).
The results show that only the intercept is statistically significant. In this case, if it's possible for all of my independent variables to be 0, does the significant intercept mean that population density would have increased/decreased regardless of the independent variables? Does having a dummy variable change that interpretation?
Solved – Only the intercept is significant in regression model (with dumthe variable?)
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Best Answer
Technically, yes. It simply means that the independent variables that you have chosen do not affect your dependent variable. But it does not mean that your dependent variable does not depend on independent variables at all. Example: Try squaring your independent variables. Does that change their coefficient's significance? If yes, then you're simply using the wrong precision of independent variables.
The dummy variable simply indicates the presence of some factor and if it's not significant, then it simply means that the dependent variable does not depend on the presence of that factor. It does not change the above interpretation.