The dataset beauty from Wooldridge contains data on wages and subjective attractiveness. Individuals were rated on a scale of 1-5 for attractiveness. . wage: hourly wage . Iwage: log(wage) . belavg: =1 if looks =4 . exper: years of workforce experience . looks: from 1 to 5 union: =1 if union member . goodhlth: =1 if good health . black: =1 if black . female: =1 if female . married: =1 if married . south: =1 if live in south . bigcity: =1 if live in big city . smilcity: =1 if live in small city . service: =1 if service industry . expersq: exper*2 . educ: years of schoolingQuestion 7 Estimate the same model, but interacting all the variables with female. Question 3 Perform a joint test on the interaction terms involving looks female : abeaug and female : bela-eg under the null hypotheses that they both are I]. Question 9 In English, explain what the joint test tells you. Question 10 Estimate image = ,39 + lleolne + 132 female + geduc + 4esper + IEEEEPBTZ + u #13 Hint: Remember looks are categorical. if You need to tell R that leeks 1.73 a faeter and net e. numeric variable. Question 11 What is the base level in the above regression? Question 12 Examine the coefficients on looks estimated in Question 10. Are they generally sensible? What looks different from what you might expect