This was an amazing video! Everything was so clearly laid out and explained! Thank you so much! I just have one question for clarification that I'm hoping to clarify. Beginning at 26:42, it is stated that the constant's value of −1.65 is the "intercept for females." My confusion is whether it reflects the value for females only or whether it reflects the value of females adjusted for education since education is also modeled? As a follow-up question, my understanding is that, just as categorical variables are held constant against their respective reference groups, continuous variables are held constant against a presumed value of 0. So, would the constant's value best be understood as reflecting the predicted intercept for females with 0 years of education? Thank you so much for any insight!
Good question. -1.65 is the intercept (the coefficient for the constant of 1) for females in the equation for wage. If you'd like to get the predicted value for wage for females, you will sum up this intercept and the coefficient on education times the value for education. If education is zero, then the intercept becomes the predicted value of wage for females, useful for plotting purposes, but it's not a realistic or useful value since education will not be zero for anyone in the sample. There is no "value of females" per se. Hope that's helpful.
This was an amazing video! Everything was so clearly laid out and explained! Thank you so much! I just have one question for clarification that I'm hoping to clarify. Beginning at 26:42, it is stated that the constant's value of −1.65 is the "intercept for females." My confusion is whether it reflects the value for females only or whether it reflects the value of females adjusted for education since education is also modeled? As a follow-up question, my understanding is that, just as categorical variables are held constant against their respective reference groups, continuous variables are held constant against a presumed value of 0. So, would the constant's value best be understood as reflecting the predicted intercept for females with 0 years of education?
Thank you so much for any insight!
Good question. -1.65 is the intercept (the coefficient for the constant of 1) for females in the equation for wage. If you'd like to get the predicted value for wage for females, you will sum up this intercept and the coefficient on education times the value for education. If education is zero, then the intercept becomes the predicted value of wage for females, useful for plotting purposes, but it's not a realistic or useful value since education will not be zero for anyone in the sample. There is no "value of females" per se. Hope that's helpful.