c.) Next, include a term in your regression capturing the interaction between gender and graduate degree. Also, include a second term in your regression capturing the interaction between gender and experience. Using this regression, predict the following: QUESTION ANSWER Predict the salary for a male working for a firm size of 245 with 15 years of experience and a graduate degree. Predict the salary for a female working for a firm size of 245 with 15 years of experience and a graduate degree. Based on this regression, is there evidence of a gender- based salary differential? What is your estimate of this differential? d.) Run a Regression Subsets on the predictors: firm_size, experience, gender, graduate degree. (Ignore the interaction terms). According to the leaps algorithm, what are the top 2 predictors? QUESTION ANSWER Predictor 1? Predictor 2