This question is based off of a hypothetical survey of entrepreneurs. There is no data set associated with this question. Each observation is an individual entrepreneur.

salary: Salary in thousands of dollars over100k: =1 if the salary is over 100k, =0 otherwise experience: Number of prior start-ups age: Age of the entrepreneur tech: Entrepreneur is in a tech industry anderson: =1 if entrepreneur is an Anderson graduate, = 0 otherwise. NOTE: Bold coefficients indicate significance at the 5% confidence level. Answer the following questions:

A) Interpret the coefficients from the following regression: salary = 40 + 20 * Anderson + 20 * Tech + 0 * Anderson * Tech

B) Interpret the coefficients from the following regression, and explain why this is a bad model: salary = 50 + 30 * Anderson * Tech

C) Interpret the coefficients from the following regressions: salary = 100 + 25 * experience on the subset where tech==1

salary = 60 + 5 * experience on the subset where tech==0

D) Consider the following regression:

salary = -75 + 40 * age Does the negative intercept mean that this regression is a bad model for predicting salary in the

survey data?