- Thread starter babaorumi
- Start date

You do not need to worry that the intercept beta0 hat is insignificant. What you need to consider seriously is the regression coefficients of each predictor variables. They must all pass the significance test. As to the intercept term, just leave it.

In some cases people are actually interested in the intercept. e.g. base performance in absence of variable x (x=0) or height of different species of offspring at birth ect ect....

In that case it certainly matters, but in 90% in the cases it isn't important as 'a little boy' states; people are mostly interested linear relationship between variables. So you need to ask yourself what do you want to know and how does the intercept fit in.

Depends on what you want to know.

In some cases people are actually interested in the intercept. e.g. base performance in absence of variable x (x=0) or height of different species of offspring at birth ect ect....

In that case it certainly matters, but in 90% in the cases it isn't important as 'a little boy' states; people are mostly interested linear relationship between variables. So you need to ask yourself what do you want to know and how does the intercept fit in.

In some cases people are actually interested in the intercept. e.g. base performance in absence of variable x (x=0) or height of different species of offspring at birth ect ect....

In that case it certainly matters, but in 90% in the cases it isn't important as 'a little boy' states; people are mostly interested linear relationship between variables. So you need to ask yourself what do you want to know and how does the intercept fit in.