1. Using data on the GPA and personal characteristics of 500 SFU students, you want to estimate the following regression: SFUGPA; = BotBiWeeklyStudy Hours; + 82 EconMajor;+ ByWeeklyStudy Hours; . Econ Major; tu; where Econ Major; is a binary indicator which takes 1 if student i is econ-major and 0 otherwise. a) How do you interpret B2? b) How do you interpret 83? c) Suppose you estimated all the values of coefficients, (Bo, B1, 82, 83). Later, you realize that students' family income could also positively affect their college GPA. Students' family income is positively correlated with their weekly hours studied. If you include their family income in your regression and re-estmate it, will the value of 81 increase or decrese compared to the previous regression? Explain clearly why you think so. d) Now you decide to include an additional binary indicator for being a native English speaker in your regression. Native; = 1 if student i is native English speaker, Native; =0 otherwise. Being a native English speaker is not correlated with hours studied but you found non- English speakers are more likely to major in economics. Being a non-native speaker has a negative effect on the college GPA. If you include the new binary regressor in your regression and re-estmate it, will the value of 82 increase or decrese compared to the previous regression? Explain clearly why you think so